United States

Department

of Agriculture

Forest Service

Rocky Mountain

Research Station

General Technical Report

RMRS-GTR-282

September 2012

Assessing the Water Needs of 

Riparian and Wetland Vegetation 

in the Western United States

David J. Cooper 

David M. Merritt
You may order additional copies of this publication by sending your 

mailing information in label form through one of the following media. 

Please specify the publication title and number.

Publishing Services

Telephone (970) 498-1392

FAX (970) 498-1122

E-mail rschneider@fs.fed.us

Web site http://www.fs.fed.us/rmrs

Mailing Address Publications Distribution

Rocky Mountain Research Station

240 West Prospect Road

Fort Collins, CO 80526

Cooper, David J.; Merritt, David M. 2012. Assessing the water needs of riparian and wetland vegetation in the western United States. Gen. Tech. Rep. RMRS-GTR-282. Fort 

Collins, CO: U.S. Department of Agriculture, Forest Service, Rocky Mountain Research 

Station. 125 p.

Abstract

Wetlands and riparian areas are unique landscape elements that perform a disproportionate 

role in landscape functioning relative to their aerial extent on the landscape. The purpose of 

this guide is to provide a general foundation for the reader in several interrelated disciplines 

for the purpose of enabling him/her to characterize and quantify the water needs of riparian 

and wetland vegetation. Topics discussed are wetland and riparian classification, characteristics and ecology, surface and groundwater hydrology, plant physiology and population and 

community ecology, and techniques for linking attributes of vegetation to patterns of surface 

and groundwater and soil moisture. 

Keywords: riparian, wetland, groundwater, water requirements, vegetation

Authors

David J. Cooper, Department of Forest, Rangeland and Watershed Stewardship, Colorado 

State University, Fort Collins.

David M. Merritt, National Watershed, Fish, Wildlife, Air, and Rare Plants Staff, USDA Forest 

Service and Natural Resource Ecology Laboratory, Colorado State University, Fort Collins.
Contents

Chapter 1: Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1

Purpose and scope . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1

Wetland and riparian concepts and definitions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3

Wetlands . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3

Riparian . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4

Wetland and riparian ecosystem types . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4

Fens . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5

Wet meadows . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7

Marshes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8

Salt flats . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9

Riparian areas . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9

Vegetation of wetland and riparian areas in the western United States . . . . . . . . . . 10

Chapter 2: Hydrologic Regime and Factors that Govern Hydrologic 

Processes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15

Landscape form and function . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26

Chapter 3: Plant Water Requirements and Vegetation Sampling . . . . . . . . . 29

How plants acquire and use water . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29

Measuring plant water relations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 32

Stomatal conductance . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 32

Xylem pressure potential . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 33

Measuring transpiration rates . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 34

Identifying plant water sources . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 36

Plant ages and growth . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 38

Patterns of plant dieback . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 41

Vegetation sampling . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 43

Woody plant recruitment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 44

Size-class structure . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 44

Condition . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 45

Chapter 4: Measurement of Surface Water and Groundwater Levels . . . . . 47

Spatial scale of analysis and monitoring . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 47

Temporal scale of analysis and monitoring . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 48

Approaches for measuring surface water and groundwater . . . . . . . . . . . . . . . . . . .49

Surface water . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 49

Groundwater . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 51

Installation of instruments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .51

Measurement . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 55

Redox potential . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 55
Data presentation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 57

Water table wells and piezometers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 57

Cross sections and profiles . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 57

Water table maps . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 59

Depth to water table map . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 62

Data management . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 62

Topographic surveying . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 63

Hydrologic study design . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 64

Groundwater-surface water interactions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 65

Hydrologic impact analysis: Groundwater pumping . . . . . . . . . . . . . . . . . . . . . . . . . 67

Hydrologic impact analysis: Changes in stream flow . . . . . . . . . . . . . . . . . . . . . . . . 70

Chapter 5: Linking Riparian and Wetland Vegetation to 

Hydrologic Factors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 73

Individual plants . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 74

Plant recruitment and establishment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 78

Growth and maintenance . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 79

Individual distributions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 80

Community analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 82

Populations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .85

Plant communities . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 86

Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 89

Chapter 6: Case Studies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 93

Case Study I: Mount Emmons iron fen, Crested Butte, Colorado . . . . . . . . . . . . . . 93

Introduction and problem statement . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 93

Background . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 93

Approach . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 94

Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 95

Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 100

Case Study II: Groundwater pumping in a riparian ecosystem, 

South Platte Park, Littleton, Colorado . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .100

Introduction and problem statement . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 100

Methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 102

Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 102

Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 104

Case Study III: Marsh hydrology, Great Sand Dunes National Park, Colorado . . 106

Introduction and problem statement . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 106

Methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 107

Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 109

Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 112

Case Study IV: Instream flow needs to support groundwater and 

riparian vegetation, Cherry Creek, Arizona . . . . . . . . . . . . . . . . . . . . . . . . . . . 113

Introduction and problem statement . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 113

Methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 114

Results and conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 115

Acknowledgments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 118

Literature Cited . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 118
USDA Forest Service Gen. Tech. Rep. RMRS-GTR-282. 2012 1

Chapter 1: Introduction

Wetland and riparian ecosystems comprise a very small percentage of the western 

U.S. land area, yet provide important economic and ecological functions (Gregory and 

others 1991, Patten 1998, Mitsch and Gosselink 2000). Wetlands provide important habitat for many species of animals, particularly amphibians, birds, and mammals 

(Nelson and others 1984, Haukos 1992, Brown and others 1996, Davidson and Knight 

2001); are local and regional centers of biodiversity (Naiman and others 1993, Pollock 

1998, Nilsson and Svedmark 2002); and provide biogeochemical, physical, and ecological processes that maintain water quality, flood attenuation, forage production for 

livestock, watershed hydrologic functioning, stream and lakeside stability, and a range 

of other valuable ecosystem services.

As the ecological importance of wetland and riparian ecosystems has become better 

understood, laws and regulations have been promulgated toward ecosystem conservation 

and management (e.g., Clean Water Act, National Environmental Policy Act, Endangered 

Species Act, and floodplain regulation). However, many wetland and riparian ecosystems in the United States have been damaged or destroyed by anthropogenic activities, 

including drainage for agriculture, dewatering and altered flow regimes by dams and 

reservoirs and groundwater pumping, stream water diversions, filling, gravel mining, 

and other activities (Tiner 1984, Patten 1998, Graf 1999, Brinson and Malvarez 2002). 

Of growing concern is the increasing human demand for water, particularly in arid and 

semiarid regions of the West. This demand is intensifying the pressure on rivers and 

their adjacent riparian areas, wetlands, and groundwater systems and is threatening the 

functioning and long-term viability of these areas (Pringle 2000, Baron and others 2002).

Purpose and scope

The U.S. Department of Agriculture Forest Service manages 193 million acres of 

National Forests and Grasslands in the United States, which includes over 400,000 miles 

of streams and rivers and 3 million acres of lakes. The National Forests are the largest 

single source of drinking water in the United States, providing 20 percent of the nation’s 

water supply. The Forest Service is responsible for balancing often conflicting multiple 

uses when managing public lands for “favorable conditions of flows” while enhancing 

the quality of life for the American public by supporting agriculture; sustaining the 

health, diversity, and productivity of the nation’s forests and grasslands; and supporting 

recreation, mining, timber harvest, energy development, and water extraction. The estimated value of water and ecosystem services provided by healthy National Forest and 

Grassland watersheds currently exceeds $7 billion annually (Brown 2004). Most U.S. 

Forest Service land management plans highlight the economic and ecological importance 

of maintaining the biological integrity of aquatic and riparian ecosystems. Meeting the 

objectives of managing the numerous activities that alter or stress freshwater ecosystems, 

while at the same time maintaining their ecological functions, is increasingly difficult 

due to the growing human demand for water. An important point often overlooked in 

conflicts over permitting land uses is that while there are benefits associated with most 

industrial, commercial, and recreational activities on public lands, there are also costs 

associated with these activities. Quantitative information about the costs and benefits 

of such activities is essential for making informed management decisions. This report 

focuses on providing tools for examining linkages between surface water, groundwater, 

and wetland and riparian vegetation. Such tools will enable managers to quantify the 
2 USDA Forest Service Gen. Tech. Rep. RMRS-GTR-282. 2012

costs and benefits of various activities associated with water, land, and river management 

as well as to examine the physical and biological responses of freshwater ecosystems 

to factors associated with climate change.

There are 2226 high head dams (greater than 7.6 m high), thousands of smaller dams 

and detention ponds, tens of thousands of water diversions, and over 90,000 water rights 

administered on public lands managed by the Forest Service. The Forest Service has 

the administrative authority to influence the flow regimes and water levels of streams 

and wetlands on public lands through: (1) the instream flow programs of some states, 

(2) input (and Section 4e authority) to the hydropower dam relicensing process managed by the Federal Energy Regulatory Commission (FERC 1920), (3) conditioning 

ditch easements (under the Ditch Bill), (4) restrictions on water extraction and related 

activities included in land management plans, and (5) terms and conditions applied to 

such grants of authorization for water diversions, including wells, to minimize damage 

to scenic and aesthetic values and fish and wildlife habitat and otherwise protect the 

environment, Federal property, and the public interest (under Federal Land Policy and 

Management Act).

Although the importance of river flow regime and wetland hydroperiod are well 

known and a variety of methods have been developed for establishing environmental 

flows for wetland riverine ecosystems (usually represented by a few species and processes), defining defensible flows and groundwater levels that are necessary to meet 

management objectives for a site or ecosystem remains challenging. Quantifying how 

much water is required to maintain desirable characteristics of a wetland, river, or riparian area requires an understanding of the relationships between flow regime and the 

ecosystem attributes being managed (Richter and others 1997, Richter and others 2003). 

This often requires an integration of available information about a site and data gathered 

in the field. Because stream reaches may be gaining (supplied by groundwater) or losing (recharging groundwater), wetlands may be influent or effluent, and water sources 

may change over time, it is necessary to understand linkages between the factors that 

influence hydrologic regime and the interactions between surface water, groundwater, 

and wetland and riparian vegetation. In many cases, this requires examination of available streamflow gauge records, land cover maps or geographic information systems, 

climatic history, remote sensing imagery, and other information as well as site-specific 

field measurement of climatic variables, stream discharge, stream and wetland stage, 

and groundwater levels.

This document will provide guidance to land managers, research scientists, and others 

tasked with understanding the hydrologic interrelationships between riverine and wetland 

ecosystems, groundwater, climate, land uses, and stressors. This work begins with a 

classification and description of major wetland types in the western United States. We 

then examine factors that influence hydrologic regime in wetlands and rivers, followed 

by a primer on plant-water relations, plant physiology, and plant and vegetation measurement techniques. Approaches to experimental design and techniques for measuring 

surface and groundwater are presented along with methods of gathering, processing, and 

analyzing data from such studies and linking attributes of wetland and riparian vegetation to hydrologic processes. We conclude with several case studies and examples of 

applications of the tools and methods presented here to systems in the western United 

States. Though this guide is tailored to the range of wetland and riparian system types 

in the western United States, the basic principles and methods presented apply to other 

regions as well.
USDA Forest Service Gen. Tech. Rep. RMRS-GTR-282. 2012 3

Wetland and riparian concepts and definitions

Wetlands

While most people are able to identify a forest or grassland as a particular vegetation 

type, wetlands are more of a challenge to identify, define, and delineate. Wetlands may 

be dominated by trees, shrubs, herbaceous plants, or mosses or they can be comprised 

of a mosaic of several of these cover types. Wetland soils range from ancient peat accumulations in high mountain valleys to recent gravel or cobble bars along streams, and 

they may be highly saline or fresh. Wetland hydrologic regimes are also varied and may 

include shallow groundwater tables or flooding created by flowing or ponded surface 

water or groundwater. This range of characteristics makes a simple definition of wetlands 

elusive. Furthermore, different definitions are appropriate for different purposes (e.g., 

administrative, functional, academic, or regulatory delineation purposes).

The definition used for Federal regulatory activities of jurisdictional wetlands in 

the western United States under Section 404 of the Clean Water Act is presented in 

the U.S. Army Corps of Engineers (COE) Manual (USACE 2009): wetlands are those 

areas that are saturated or inundated at a frequency and duration sufficient to support 

and that under normal circumstances do support a prevalence of vegetation typically 

adapted for life in saturated soils. According to this definition, wetlands are saturated 

or inundated by surface water or groundwater often enough and long enough during the 

growing season that they support wetland plants. A key tenet of wetland identification 

using the COE manual is application of the three parameter approach. Jurisdictional 

wetlands must have positive indicators of each of the three parameters: (1) hydrophytic 

vegetation, (2) wetland hydrologic regimes, and (3) hydric soils. Hydrophytes—plants 

with morphological or physiological adaptations for life in saturated soils—are listed 

in the U.S. Fish and Wildlife Service National Wetlands Inventory “List of Plant Species that Occur in Wetlands” (Reed 1988, Lichvar and Kartesz 2012). Hydric soils are 

gleyed, or mottled, or may have peat accumulation as described in the COE manual. 

Hydrologic regimes of wetlands often create flooding, ponding or soil saturation in the 

upper 30.5 cm of soils for at least two weeks during the growing season, as presented 

in the COE manual and recent regional supplements (USACE 2009).

A second widely used definition of wetlands was developed by the U.S. Fish and 

Wildlife Service for the National Wetlands Inventory mapping program (Cowardin and 

others 1979): wetlands are lands transitional between terrestrial and aquatic systems 

where the water table is usually at or near the surface or the land is covered by shallow water. For purposes of this classification wetlands must have one or more of the 

following three attributes: (1) at least periodically, the land supports predominantly 

hydrophytes, (2) the substrate is predominantly undrained hydric soil, and (3) the 

substrate is non-soil and is saturated with water or covered by shallow water at some 

time during the growing season of the year. The concept of wetland presented in this 

definition is broader than the COE definition, as only one of the three parameters need 

be present for a site to be classed as a wetland. Hydrophytes are plants listed by Reed 

(1988), hydric soils are defined similarly to the COE, and non-soils are areas that do 

not support plants because they are too saline, flooded too deeply, or are bare sediment.

Wetland definitions have also been developed by the National Research Council 

(National Research Council 1995), other Federal agencies such as the Natural Resources 

Conservation Service, and different regions of the U.S. Forest Service and Bureau of 

Land Management. All wetland definitions recognize, to one degree or another, the key 

role of hydrologic processes (e.g., inundation timing, periodicity, and depth) in wetland 

formation and the resulting suite of distinctive soil and vegetation characteristics.
4 USDA Forest Service Gen. Tech. Rep. RMRS-GTR-282. 2012

For this report, we consider wetlands to be ecosystems that have saturated and anoxic 

soils for at least two weeks during the growing season over many years.

Riparian

The term riparian has been variously defined and applied for legal, regulatory, and 

ecological contexts. The term originates from the Latin word riparius, which means 

of or pertaining to the bank of a river and is both a geographic concept identifying 

lands adjacent to streams as well as a hydrologic, geomorphic, and ecological concept 

identifying sites that are hydrologically and geomorphically influenced by the flowing 

water of streams. The definition we apply in this assessment closely follows that used 

by Naiman and Décamps (1997): it is the portion of the stream channel occurring between the low and high water marks and adjacent terrestrial areas extending from the 

high water mark toward the uplands where vegetation may be influenced by elevated 

water tables or flooding. A key element of this definition is the existence of a physical hydrologic and geomorphic connection, at least intermittently, between the stream 

and riparian area. In the case of ephemeral streams, this connection may be infrequent 

and limited to the physical effects of isolated flood events. In contrast, along perennial 

streams, the stream exerts a more constant and dominant control on ecological function 

through flooding as well as by influencing water table dynamics. Riparian ecosystems 

have unique geomorphic characteristics, hydrologic regimes, landforms, biota, and 

ecological processes that distinguish them from aquatic, isolated wetland, and upland 

ecosystems.

There are a number of characteristics common to all riparian ecosystems. The first 

is the periodic or perennial influence of flowing water. Flood events are key drivers of 

geomorphic, biogeochemical, and biological characteristics of riparian areas (Bowden 

1987, Knighton 1998, Pinay and others 2002, Arscott and others 2003) and act to differentiate riparian from other wetland and non-wetland ecosystem types. Riparian areas 

typically have shallow water tables when compared to adjacent uplands and support 

distinct vegetation types (Carsey and others 2003), in both perennial and many 

ephemeral streams (Shaw and Cooper 2008).

Wetland and riparian ecosystem types

Hydrologic regime is the daily, weekly, seasonal, and interannual pattern of flooding, 

inundation, water table dynamics, and/or soil saturation of a wetland, river, or stream. 

The hydrologic regime is a function of watershed- and local-scale climate and physical processes that provide water to a site and influence soil conditions and plant water 

availability. It also includes annual, interannual, and seasonal flooding, ponding or water 

table depth variation, the ability of water to transport sediment and dissolved materials 

and nutrients on a seasonal and long-term basis, and the rate of change in transitioning 

from seasonal high to low water levels. The hydrologic regime of a wetland influences 

the wetland type and its ecological functioning more than other factors. For example, it 

influences ecosystem productivity, decomposition of organic matter, mineral sediment 

erosion and deposition, seasonality of drought, depth of flooding (Pinay and Naiman 

1991, Mitsch and Gosselink 2000, Weltzin and others 2000), rates of denitrification (Pinay and others 2007), and site biotic composition (Cooper and Andrus 1994, 

Seabloom and others 1998). At local scales, the hydrologic regime operates as a driver 

of ecological structure and function, facilitating peat accumulation or mineral sediment 
USDA Forest Service Gen. Tech. Rep. RMRS-GTR-282. 2012 5

deposition to create landforms, while at larger scales it shapes landscape-scale patterns 

of wetland and riparian ecosystem abundance and distribution. Collectively, climate, 

geology, and hydrologic regime structure the template from which wetlands and riparian 

ecosystems form, develop, and function.

There are five main inland wetland and riparian ecosystem types in the western United 

States, and they vary in their relative abundance, distribution on the landscape, vegetation 

composition, structure and dynamics, and functional characteristics. These types are: 

(1) fens, (2) wet meadows, (3) marshes, (4) salt flats, and (5) riparian areas. Each type 

can also be subdivided based upon hydrologic regime, vegetation, geochemistry, and 

other factors into a number of different subtypes, typically defined by dominant plants, 

plant associations, or communities. Although frequently managed and regulated as a 

single resource, wetland and riparian ecosystem types differ widely in their hydrologic 

regimes and processes, vegetation, and functional characteristics and in their responses 

to stresses posed by humans and natural disturbances. The processes occurring within a 

wetland or river are typically not controlled, thus they cannot often be managed, at the 

scale of the site. Conditions and activities that influence water and sediment within the 

contributing groundwater and surface watershed must be considered.

Fens

Fens have perennial groundwater inflows that maintain water tables at or near the 

ground surface. This constant saturation retards the decomposition of organic matter and 

allows for peat accumulation. Being groundwater driven, fens vary considerably in the 

chemical content and pH of the source water. The chemical composition of groundwater 

is controlled by the mineral composition of bedrock and unconsolidated sediments in the 

contributing watershed. Fens form in a variety of landscape settings and are among the 

most floristically diverse ecosystems in the region, and many support rare and widely 

disjunct species (Cooper and Andrus 1994, Cooper 1996, Cooper and Sanderson 1997, 

Chadde and others 1998, Weber 2001, Bedford and Godwin 2003, Hiedel and Laursen 

2003). In contrast to riparian areas, little mineral sediment generally moves into or out 

of fens, and they are geomorphically stable on a time scale of millennia. Fens may occur 

within or adjacent to riparian areas or other wetland types in valley bottoms, but they 

have independent groundwater sources and are not dependent directly upon stream water. 

Fens are typically dominated by herbaceous monocots in the family Cyperaceae (sedge 

family) and may have a continuous carpet of mosses. However, some fens have a canopy 

of shrubs or conifer trees. Fens have formed in a variety of landforms, including slopes 

and basins, and create landforms such as floating mats, hummocks, strings, and pools 

through the process of peat accumulation. Fens provide critical habitat for amphibians, 

many small mammals, aquatic invertebrates, and passerine birds (Figure 1-1).

Most fens have formed in locations where groundwater discharges to the surface. 

These are the most stable spring complexes in the region, and plants colonize these 

springs, blanketing the water source with layers of roots, rhizomes, leaf and stem litter, and other undecomposed plant remains that form the peat bodies. The water flows 

vertically up through the peat body and laterally through layers within the peat. Some 

peatlands have sheet flow across their surfaces in early through mid-summer, others 

have distinctive water-tracks, while others rarely have surface water. Fens that formed 

in basins may have pools or ponds that are being encroached upon by floating mats that 

will eventually fill the basin with peat.
6 USDA Forest Service Gen. Tech. Rep. RMRS-GTR-282. 2012

Figure 1-1. Fens. (A) is East Lost Park in the Taryall Mountains, Colorado. (B) is Green Mountain 

Trail pond fen with a floating mat in Rocky Mountain National Park, Colorado. (C) is High Creek 

fen, an extremely rich fen in South Park, Colorado. (D) is Drosera fen in Yosemite National Park, 

California. (E) is Long Meadow in Rocky Mountain National Park, Colorado.

A

C

B

D

E
USDA Forest Service Gen. Tech. Rep. RMRS-GTR-282. 2012 7

Figure 1-2. Wet meadows. (A) is Convict Creek valley, Sierra 

Nevada, California. (B) is Log Meadow in Sequoia National 

Park, California. (C) is in the San Luis Valley, Colorado. (D) is 

a meadow at the foot of Great Basin range, Nevada. 

A

C

B

D

Wet meadows

Wet meadows are widespread and likely cover more area in the mountainous western United States than all other wetland types combined. They occur from alpine areas 

to plains and from intermountain parks and basins to foothills. Despite their relative 

abundance, few studies have examined their hydrologic and edaphic characteristics or 

vegetation dynamics. Although wet meadows typically have seasonally saturated soils, 

they lack the perennial high water tables of fens or the large seasonal and inter-annual 

water table fluctuations of marshes, and they do not form peat soils. Many natural wet 

meadows are managed for livestock forage and hay production, and in agricultural 

areas, wet meadows have been created by application of water from ditches. Most wet 

meadows are dominated by herbaceous plants, particularly Juncus arcticus, Carex 

nebraskensis, and C. lanuginosa. Woody plants, such as Pentaphylloides (Potentilla) 

floribunda (cinquefoil) and a number of Salix (willow) species, may also be present 

(Figures 1-2A through D).
8 USDA Forest Service Gen. Tech. Rep. RMRS-GTR-282. 2012

Marshes

Marshes form in depressions and include such diversely named regional wetland types 

as prairie potholes, playas, vernal pools, lacustrine fringes, and oxbow lakes on river 

flood plains (Figure 1-3). Marsh hydrologic regimes are variable, with both prolonged 

periods of inundation and desiccation (Winter and Rosenberry 1998, Winter and others 

2001). Marshes periodically have deep standing water (>1m), which limits the species 

that occur to aquatic and wetland species tolerant of submersion or deep inundation. 

Because some marshes are terminal basins with surface water inflows but little or no 

outflow, their chemical content varies from freshwater to saline and this influences plant 

and animal species composition, litter decomposition rates, and productivity of plants, 

aquatic invertebrates, and larger animals (Thormann and others 1999). Hydrologic 

variability, water depth, and salinity are key factors determining the species composition of marshes, both spatially within and among marsh complexes and temporally 

from wet to dry climate periods (van der Valk and others 1994, Seabloom and others 

1998, Smith and Haukos 2002). Seed banks play a particularly important role in marsh 

vegetation dynamics (van der Valk and Davis 1976, Smith and Kadlec 1983, Wilson 

and others 1993), with large fluctuations in species composition commonly occurring 

over relatively short time scales. The large water depth gradients also generate distinct 

vegetation zonation patterns in many marshes (Johnson and others 1987, Lenssen and 

others 1999), and their diverse hydrologic regimes and vegetation types provide critical 

habitat for waterfowl, shorebirds, and amphibians.

Figure 1-3. Marshes. (A) is bulrush-dominated marsh with prominent zonation near Denver, Colorado. (B) is large marsh with 

fringing vegetation and floating bulrush clones in North Dakota. (C) is marsh on Yellowstone National Park’s northern range, 

Wyoming. (D) is Heart Lake marsh in Yellowstone National Park, Wyoming.

A

C

B

D
USDA Forest Service Gen. Tech. Rep. RMRS-GTR-282. 2012 9

Salt flats

Salt flats are widespread at low elevations through the West, particularly in intermountain basins (Figure 1-4). They form where high soil salt concentrations occur near the 

soil surface. The two main processes that promote salt flat formation are surface water 

evaporation from basins with fine-textured soils, and evaporation from the capillary 

fringe of a shallow water table that leads to salt accumulation on the soil surface. The 

combination of high salt concentrations and saturated soils creates difficult growing 

conditions for plants; consequently, plant cover and productivity are typically low, and 

vegetation composition is limited to species tolerant of both high salt concentrations 

and saturated soils (Dodd and Coupland 1966, Ungar 1966, Ungar 1974). Salt flats 

may also occur in saline soils on river floodplains, particularly along rivers that rarely 

experience overbank flooding due to upstream dams or diversions (Jolly and others 

1993). Ironically, because salt flats are marginal for forage production and are unsuitable for crops, they have been spared many of the anthropogenic impacts affecting other 

wetland types, other than dewatering. Salt flats are typically dominated by grasses such 

as Distichlis spicata (salt grass), Sporobolus airoides (alkali sacaton), Spartina gracilis 

(cordgrass), and herbaceous dicots such as Triglochin maritimum (arrow grass) and other 

halophytes, many of which also occur in coastal salt marshes. When flooded, salt flats 

support high densities of aquatic invertebrates and are important habitat for migratory 

waterfowl and shorebirds.

Riparian areas

Riparian ecosystems have diverse landforms, stream sizes, valley gradients, hydrologic regimes, vegetation, and ecological functions. They vary from low-gradient water 

tracks running adjacent to peatlands at high elevations; to steep-gradient, small-order 

headwater mountain streams; to ephemeral streams in mountain foothills; to those along 

broad, low-gradient alluvial rivers in the Great Plains (National Research Council 2002). 

Figure 1-4. Salt flats. (A) is in the San Luis Valley, Colorado. 

(B) is in North Park, Colorado.

A B
10 USDA Forest Service Gen. Tech. Rep. RMRS-GTR-282. 2012

The principal characteristic unifying riparian ecosystems is the presence of moving 

water, which has the potential to erode, transport, and deposit sediment and to create 

distinctive landforms such as point bars, floodplains, and abandoned channels. These 

landforms and the fluvial processes that influence their creation, destruction, and turnover 

are critical for the establishment and persistence of riparian plants.

The energy of flowing water is a key variable influencing riparian structure and 

function. The frequency, magnitude, and energy of floods, which vary widely due to 

differences in basin size, topography, and climatic regime, affect all ecological processes 

from nutrient cycling to plant establishment to rates of channel migration, floodplain 

development, and riparian forest formation and turnover (Karrenberg and others 2002, 

Cooper and others 2003a, Adair and others 2004).

The hydrologic regimes of streams also vary widely and provide important constraints 

and opportunities for riparian and aquatic organisms. Though all streams receive multiple 

sources of water over time, streams may be broadly divided into classes based upon the 

dominant sources of water that influence the hydrologic regime (Poff 1996). Hydrologic 

regimes of riparian areas vary from relatively stable, groundwater-driven flows, such 

as those in the Nebraska Sandhills (Bio/West 1986, Winter 1999), to infrequent and 

unpredictable flash floods associated with ephemeral streams located throughout the 

mountainous and semiarid western United States (Friedman and Lee 2002, Shaw and 

Cooper 2008).

Seasonal flooding may be governed by frontal weather systems, monsoons, convective storms, or seasonal changes in temperature that govern snowmelt regimes (Wohl 

2000). An understanding of the sources of flow to a stream, the magnitude and frequency 

of those flows, and the seasonal and interannual timing in those flows is important in 

understanding principal forces that govern species composition, turnover, and ecological functioning of riparian areas and their potential responses to changing stream flow 

or groundwater regimes.

Many riparian areas are dominated by woody plants, in particular by species of 

Populus (cottonwood) at the lowest elevation and Salix species at all elevations. At mid 

elevations, species of Alnus (alder) and Betula fontinalis (birch) may be common. The 

smallest springs and brooks may be dominated by herbaceous plants, including species 

of Mertensia (blue bells), Glyceria (mannagrass), Senecio (groundsel), and Mimulus 

(monkey flower). In more arid regions such as the Sonoran desert, riparian areas may be 

characterized as forests dominated by species of Juglans (walnut), Platanus (sycamore), 

Populus, Salix, Prosopis (mesquite) and Fraxinus (ash) (Figure 1-5).

Vegetation of wetland and riparian areas in the western United States

Wetlands and riparian areas support a variety of plant species and community types 

found nowhere else in the West. For example, 183 (31%) of the nearly 600 ecological 

system types (groups of plant community types that co-occur in similar ecological settings) defined by Comer and others (2003) in their analysis of Rocky Mountain region 

vegetation are wetlands, even though wetlands occupy only 1 to 2 percent of the western 

landscape.

In order to understand the range of wetland forms throughout the western United 

States, we compiled vegetation data from 5266 wetland and riparian plots from the Rocky 

Mountain region (including the Great Plains). To understand the structure and variety 

of wetlands represented in this large data set and to see relative relationships between 

wetland types, we performed an indirect ordination on the riparian and wetlands plots 

(Figure 1-6) using detrended correspondence analysis (DCA; McCune and Mefford 

1999). Plot data include species composition and percent canopy coverage by species. 
USDA Forest Service Gen. Tech. Rep. RMRS-GTR-282. 2012 11

Figure 1-5. Riparian areas. (A) is small, glaciated stream valley on east side of Wind River Range, Wyoming. (B) is subalpine 

stream in Rocky Mountain National Park, Colorado. (C) is the Blue River downstream from Dillon, Colorado. (D) is Yampa River 

in Deer Lodge Park, Colorado. (E) is Lithodendron Creek in Petrified Forest National Park, Arizona.

A

C

B

D

E
12 USDA Forest Service Gen. Tech. Rep. RMRS-GTR-282. 2012

Figure 1-6. Detrended Correspondence Analysis (DCA) ordination of wetland and riparian communities. The location of major wetland 

communities are identified in the graph. The main direction of environmental variation is shown using arrows. Centroids of diagnostic 

and common plant species are shown using the following abbreviations: CARNIG = Carex nigricans, DREADU = Drepanocladus 

aduncus, ELEQUI = Eleocharis quinqueflora, KALPOL = Kalmia polifolia, CARILL = Carex illota, TOMNIT = Tomenthypnum nitens, 

BETFON = Betula fontinalis, CARSCO = Carex scopulorum, SALPLA = Salix planifolia, CARVES = Carex vesicaria, SENTRI = 

Senecio triangularis, CARAQU = Carex aquatilis, CARUTR = Carex utriculata, CALCAN = Calamagrostis canadensis, SALMON 

= Salix monticola, SALGEY = Salix monticola, DESCES = Deschampsia cespitosa, PENFLO = Pentaphylloides floribunda, PICPUN = Picea pungens, BETGLA = Betula glandulosa, POPANG = Populus angustifolia, SALIRR = Salix irrorata, CARSIM = Carex 

simulata, JUNARC = Juncus arcticus, SALEXI = Salix exigua, CARNEB = Carex nebraskensis, CIRCAN = Cirsium canadensis, 

AGRGIG = Agrostis gigantea, BROINE = Bromopsis inermis, NEGACE = Negundo aceroides, ULMAME = Ulmus americanus, 

POPDEL = Populus deltoides, ELEANG = Eleagnus angustifolia, PHRAUS = Phragmites australis, SPAEUR = TAMRAM = Tamarix

spp., PASSMI = Pascopyrum smithii, PUCAIR = Puccinellia airoides, SUACAL = Sueda calcioliformia, SARVER = Sarcobatus 

vermiculatus, BOLMAR = Bolboschoenus maritimus, DISSTR = Distichlis stricta, AMPNEV = Amphiscirpus nevadensis, SPOAIR 

= Sporobolus airoides, GLAMAR = Glaux maritimus, TRIMAR = Triglochin maritimum, SCHPUN = Schoenoplectus pungens, ELEPAL = Eleocharis palustris, SPAPEC = Spartina pectinatus, GLYGRA = Glyceria grandis, BECSYZ = Beckmannia syzygachne, 

TYPLAT = Typha latifolia, SCHLAC = Schoenoplectus lacustris, SPAEUR = Sparganium eurycarpum. 
USDA Forest Service Gen. Tech. Rep. RMRS-GTR-282. 2012 13

DCA places observations (vegetation plots) in a multi-dimensional ordination space, 

with plots with the most similar floristic composition occurring close to each other, 

and those most dissimilar being farthest apart. The axes are in standard deviation units, 

with 200 to 400 units indicating a complete species turnover; for example, a plot at 100 

on axis 1 (x-axis) and a plot at 500 on axis 1 would likely have no species in common.

Variation in species composition along axis 1 represents an increase in elevation and 

an increase in water table permanence (from right to left). High-elevation sites with 

perennially high water tables occur on the left, and low-elevation sites with varying 

water tables occur on the right. Variation in axis 2 appears to be driven by water chemistry, with saline sites near the top and freshwater sites toward the bottom. Each plot is 

represented by one point, and the centers of abundance of key indicator plant species 

are shown in the ordination space.

The five major wetland types break out distinctly in the ordination space. Fens are on 

the far left, salt flats are on the top right, marshes are on the bottom right, wet meadows 

are on the bottom center, and riparian areas are along a band that extends from the top 

right to the left. The riparian continuum includes springs and small headwater mountain 

streams with herbaceous communities dominated by species such as Senecio triangularis, 

Salix geyeriana, and other Salix-dominated thickets (also called carrs) along small- to 

medium-sized mountain rivers, Populus angustifolia (narrowleaf cottonwood)- and 

Picea pungens (blue spruce)-dominated forests along mid-elevation mountain rivers, 

Acer negundo (box elder) forests in canyons, and Salix irrorata and Populus deltoides 

forests with Tamarix (salt cedar) and Elaeagnus angustifolia (Russian olive) along 

foothills and plains streams.

A range of fen types are separated in the ordination, including basin fens dominated 

by sedges such as Carex utriculata and Carex vesicaria; sloping fens dominated by 

Eleocharis quinqueflora (spike rush), Carex aquatilis, and Carex illota; and wooded 

fens with Kalmia polifolia (swamp laurel) and Salix planifolia. There are a range of 

wet meadows dominated by Deschampsia cespitosa (tufted hairgrass) at high elevation, 

Juncus arcticus (arctic rush) at mid to low elevation, and Carex nebraskensis at the 

lowest elevations. A wide range of marshes occur, and due to the deep water, many are 

monocultures or have very low floristic diversity, creating a wide spread in the plots. 

The deepest water sites have Schoenoplectus lacustris (bulrush) and Typha latifolia 

(cattail), while more shallow water sites are dominated by Eleocharis palustris and 

Schoenoplectus pungens (three-square). The latter species can also occupy marshes 

that are highly saline and plot adjacent to salt flats. The salt flat communities are also 

species poor, and many monocultures occur.
14 USDA Forest Service Gen. Tech. Rep. RMRS-GTR-282. 2012
USDA Forest Service Gen. Tech. Rep. RMRS-GTR-282. 2012 15

Chapter 2: Hydrologic Regime and Factors 

That Govern Hydrologic Processes

The principal source of water supplying most streams, groundwater, and wetlands 

is precipitation in the form of rain and snow. Five main hydrologic processes influence 

all riparian and wetland ecosystems: (1) the amount, timing, and type of precipitation, 

(2) groundwater recharge, (3) groundwater discharge, (4) surface water runoff, including 

stream flow, and (5) evapotranspiration (Figure 2-1). Regions with higher total annual 

precipitation typically have higher annual stream flows, a higher proportion of perennial 

streams, and, in many areas, perennial groundwater flow systems (Lins 1997).

Figure 2-1. Components of the hydrologic cycle that influence riparian and wetland ecosystems, 

including precipitation, runoff and river flow, groundwater flow, and evaporation and evapotranspiration.
16 USDA Forest Service Gen. Tech. Rep. RMRS-GTR-282. 2012

Surface water runoff occurs whenever the rate of water delivery to soils—from precipitation, snowmelt, or groundwater discharge—exceeds the rate and capacity of the 

soil for infiltration. Infiltration rates are influenced by soil texture and structure, depth 

to bedrock, vegetation, and soil bioturbation. Shallow bedrock or permafrost forms a 

confining or impermeable layer that slows or detains groundwater, which leads to pooling. Coarse textured soils and those with high porosity and/or abundant macropores 

generally have higher infiltration rates and higher hydraulic conductivity. Vegetation can 

slow the flow of surface water over the land surface and facilitate infiltration. Groundwater recharge is the process of water infiltrating through the soil profile to a local or 

regional water table. The water table is the top of the most shallow groundwater flow 

system. Below the water table, soils are saturated; above the water table, the soils are 

unsaturated and under tension. Groundwater is present beneath most landscapes where 

there is shallow bedrock or thick deposits of unconsolidated material such as moraine, 

alluvium, or colluvium underlain by an impermeable layer.

Groundwater flows along pressure gradients and discharges to the ground surface 

where the water table intersects the soil surface. Groundwater discharge may be caused 

by physical features such as a decrease in depth to bedrock, which forces groundwater 

to the surface, or a reduction in land slope that reduces the rate of groundwater flow 

causing the water table to rise. Groundwater discharge may occur at a point, which is 

typically termed a spring, but it may also occur along broad seepage faces (e.g., along 

a valley wall) or beneath streams, lakes, or fens. Surface water and groundwater are 

subject to evaporation as well as transpiration by plants, and the combined loss of water 

to the atmosphere is termed evapotranspiration (ET).

The distribution, abundance, and types of wetland and riparian ecosystems that occur 

within a watershed are linked to and dependent upon water availability. Precipitation 

varies dramatically across the western United States, with the highest annual precipitation totals occurring west of the Cascade Range and Sierra Nevada and in some high 

mountain regions occurring in the Great Basin and Rocky Mountains (Figure 2-2A). 

Annual precipitation totals also vary markedly along elevation gradients, even over short 

distances due to orographic lift, producing higher precipitation totals on mountains, with 

rain shadows forming in the leeward side of mountains. High mountain watersheds may 

receive five times more precipitation than valleys and basins, as illustrated for North 

Park and the Park Range in northern Colorado (Figure 2-2B). Winter storms typically 

move from the Pacific Ocean to the east, and west-facing mountain slopes receive higher 

precipitation totals than eastern slopes, as occurs in the Sierra Nevada and Cascades.

The seasonality of precipitation also varies across the region. The far west and northern 

Rocky Mountains receive mainly winter precipitation. On the Great Plains, the precipitation peak is in spring and early summer from air masses moving north from the Gulf 

of Mexico (Figure 2-2C). In the Southwest, including the southern Rocky Mountains, 

there is a winter peak and a second late summer monsoon precipitation (rain) peak. The 

seasonality of precipitation, along with the temperature-controlled timing of snowmelt, 

influences the pattern of stream flow, groundwater recharge and discharge, and surface 

runoff that fills basins.

A deep snowpack may accumulate in high mountain regions from October through 

April and melt in spring to produce a snowmelt-driven flow peak and an important 

period of groundwater recharge (Figure 2-3). Once the watershed snowpack has 

melted, streamflow is supported by groundwater discharge and runoff from precipitation events; lower stream flows occur during most of the summer. The majority 

of snowmelt-driven streams are relatively small and occur at high elevations, however, 

they feed the relatively few perennial regional streams. Some perennial rivers in the 

southwestern United States have high flow events due to both snowmelt and monsoon 

rains, as illustrated by the San Miguel River in southwestern Colorado (Figure 2-3). 
USDA Forest Service Gen. Tech. Rep. RMRS-GTR-282. 2012 17

Figure 2-2A. Average annual precipitation for the western United States (http://www.wrcc.dri.edu/pcpn/

westus_precip.gif).

A
18 USDA Forest Service Gen. Tech. Rep. RMRS-GTR-282. 2012

Figure 2-2B. Average annual precipitation for Colorado. Arrow points to North Park, a low-elevation basin surrounded by 

mountains. The Park Range on the west side of North Park receives approximately five times the average annual precipitation as the Park floor. 

B

Figure 2-2C. Percentage of winter (top left), spring (top right), and late summer (bottom) 

precipitation for the western United States.

C
USDA Forest Service Gen. Tech. Rep. RMRS-GTR-282. 2012 19

Figure 2-3. (Top left) Snow water equivalent (SWE) (blue line) in inches at the Snake River station, Wyoming, for 2006. Red 

line is total cumulative precipitation in 2006, orange is mean cumulative precipitation for 1971 to 2000, and grey is mean 

cumulative SWE for 1971 to 2000. (Top right) Mean daily discharge of the Snake River at the Flagg Ranch, Wyoming, showing the timing of stream peak flow relative to snowpack at the Snake River snow course. (Center left) Mean daily flow for the 

San Miguel River, Uruvan, Colorado, showing an early summer snowmelt runoff peak with additional monsoon rain peaks in 

August, September, and October. (Center right) Niobrara River, Sparks, Nebraska, showing that river stage height for this 

spring-fed river varies little. Bottom left: Puerco River at Chambers, Arizona, is an ephemeral stream flowing only following 

snowmelt, or rain events. In 2008, there were three large snowmelt-driven floods in January through February and six monsoon rain-driven floods in late summer. 
20 USDA Forest Service Gen. Tech. Rep. RMRS-GTR-282. 2012

Ephemeral streams flow only following runoff events, triggered by either snowmelt or 

summer rainstorms or both, as illustrated by the Puerco River in Arizona (Figure 2-3). 

Other streams may be spring-fed (groundwater supported) and have little annual variation, as illustrated by the Niobrara River in Nebraska (Figure 2-4).

Most streams are connected to and interact with groundwater systems. Most perennial 

streams are fed by surface runoff as well as groundwater, the latter of which sustains 

flow during periods lacking precipitation or snowmelt. Streams may gain groundwater 

through their banks and from under their bed, and are termed gaining streams, as their 

flow increases as it moves downstream due to groundwater inputs (Figure 2-5: top panel). 

Streams may also lose water from their bed and banks to the groundwater system, and 

are termed losing streams, as their surface flow decreases in a downstream direction 

(Figure 2-5: middle panel). Many losing streams are intermittent or ephemeral in at least 

some reaches. Many streams are gaining in some reaches and losing in other reaches, 

supporting very different environments in the stream and on the floodplains. Some 

ephemeral streams in arid regions with deep water tables, or those on bedrock, are not 

connected to the water table (Figure 2-5: bottom panel). The relationship of a stream 

and the local or regional water table will influence stream and riparian zone functions.

Valley form (width, slope, and depth to bedrock) may influence whether a stream is 

gaining or losing along its length. As valleys narrow in a downstream direction, groundwater may upwell, causing the stream to gain groundwater and flow on the surface or 

increase in volume (Figure 2-6). As valleys widen, surface water may be lost to the 

deeper, wider alluvium, and the stream may decrease in volume or disappear completely 

as water infiltrates into the groundwater. This process of valley-controlled gaining and 

losing may result in secondary biogeochemical processes that can influence ecological patterns on the landscape, such as the presence of particular riparian communities 

(Harner and Stanford 2003).

Figure 2-4. Typical discharge patterns for a range of rivers. Rivers originating in the high mountains such as the 

Animas and Shoshone have large, snowmelt-dominated peak discharges. In contrast, flood flows along Great Plains 

rivers such as the Cimarron and Cheyenne are driven principally by rain events and are frequently less predictable 

and more “flashy” in nature. The Niobrara River and other rivers in the Sandhill region of Nebraska have continuous 

groundwater inputs with relatively constant stream discharge. 
USDA Forest Service Gen. Tech. Rep. RMRS-GTR-282. 2012 21

Figure 2-5. Connections of streams and groundwater (modified from Winter and others 1996).

Figure 2-6. Valley form may influence whether a reach is gaining or losing. Where valleys narrow, groundwater may upwell 

and result in gaining stream reaches; where valleys widen, streams may lose water to deeper and wider alluvium. This pattern 

may be revealed by higher abundance and productivity of riparian vegetation in upwelling valley segments. From Harner and 

Sanford (2003).
22 USDA Forest Service Gen. Tech. Rep. RMRS-GTR-282. 2012

Riparian vegetation along gaining and losing stream reaches may respond differently 

to altered flow regimes. Small changes in streamflow may have significant effects on 

riparian vegetation along a losing reach, whereas gaining reaches may have limited 

effects from certain altered flow regimes.

Wetlands form where surface water ponds or where groundwater saturates soils. In 

the prairie pothole region of North Dakota, rain and snowmelt runoff fills basins 

(Figure 2-7) where groundwater recharge occurs. Groundwater flow paths may connect 

basin A through basin B to basin C (Figure 2-7). Basin A is likely to be intermittently 

flooded, while the long groundwater flow path may produce perennial saturation or 

inundation in basins B and C. Because basin B has water flow through, it does not accumulate salts; then again, basin C is a terminal basin with water leaving by evaporation, 

and high salt concentrations may occur. The complex recharge, groundwater flow, and 

discharge patterns produce a range of wetland types. Recharge basins (A) support fresh 

water marshes, flow through basins (B) may be peat accumulating fens, and discharge 

areas (C) may support salt marshes. The range of wetland types and the chemistry of 

surface water and groundwater will vary depending upon the bedrock or surficial material that water flows through and the availability and the availability and solubility of 

salts and other materials.

Four wetland hydrologic regimes can be conceptualized: (1) groundwater depression wetland, (2) groundwater slope wetland, (3) surface water depression wetland, and 

(4) surface water slope wetland (Novitzki 1982: Figure 2-8). Groundwater depression 

wetlands form in basins that intercept the regional or local water table. If the groundwater 

flow is seasonal or if water levels vary, the wetland likely will be a marsh (Figure 2-8: 

top left panel; Figure 2-9: top panel). If the flow is perennial, without considerable 

annual and interannual variation, a fen will likely form. Groundwater slope wetlands 

form where groundwater discharges at a geologic discontinuity or toe slope, and wet 

meadows or fens are formed (Figure 2-8: top right). Where surface flows occur in channels, riparian zones may develop (Figure 2-8: bottom right). Surface water slopes can 

also form on the fringes of lakes (Figure 2-9). Surface water depressions are formed by 

overland flow or as terminal sumps for streams and would form marshes or salt flats 

(Figure 2-8: bottom left panel).

Figure 2-7. Surface water and groundwater flow in complex, glaciated terrain. Precipitation 

runoff fills ponds (A) that recharge groundwater that flows through basin B and discharges into 

basin C. Modified from Winter (1989). 
USDA Forest Service Gen. Tech. Rep. RMRS-GTR-282. 2012 23

Figure 2-9. Geomorphic settings for marsh 

development. Arrows indicate principal water 

fluxes of water. Modified from Brinson and 

Malvarez (2002).

Figure 2-8. Hydrologic processes supporting four main wetland types. Modified from 

Novitzki (1978).
24 USDA Forest Service Gen. Tech. Rep. RMRS-GTR-282. 2012

Salt flat wetlands may form through several hydrologic processes. Salt accumulates 

in wetlands associated with seasonal ponds that occur on low-permeability soils or 

seasonally flooded lake margins (Figure 2-10A). Salt also accumulates where groundwater discharges to the soil surface (Figures 2-10B and C) or is elevated by capillary 

rise and evaporates, or it occurs where the capillary fringe reaches the surface and water 

evaporates (2-10D). High salt accumulation can only occur where flow does not remove 

salts from a site, and in such places, salt may accumulate even when source water has 

low ion concentrations (Jolly and others 1993).

Figure 2-10. Schematic illustrations of different hydrogeomorphic settings that create salt flats. Ponds create 

salt accumulation where they dry seasonally or where the surface water-supported water table is close to the 

soil surface (A). Salt also accumulates where groundwater discharges to the surface and evaporates (B and 

C), or where capillary water reaches the soil surface (D). Modified from Alberta Agriculture and Food (2004).

C D

A B
USDA Forest Service Gen. Tech. Rep. RMRS-GTR-282. 2012 25

One approach to the classification of wetlands, the hydrogeomorphic system, provides 

a classification based upon site properties (Brinson 1993). Indicators of function are 

discussed as derivatives of the three basic properties along with the ecological significance of each of the properties. The core of the classification has three components: (1) 

geomorphic setting, (2) water source and its transport, and (3) hydrodynamics. Geomorphic setting is the topographic location of the wetland within the surrounding landscape. 

Water sources can be simplified to three: precipitation, surface or near-surface flow, and 

groundwater discharge. Hydrodynamics refers to the direction of flow and strength of 

water movement within the wetland. While the three components are treated separately, 

there is considerable interdependency. Such redundancy may be useful where it reduces 

errors in interpretation and reinforces the underlying principles that explain wetland 

functions. As shown in Table 2-1 (Smith and others 1995), there are a number of different 

hydrogeomorphic classes, several of which occur in the western United States. Riverine 

wetlands occur along streams; depressional wetlands form in basins and typically are 

marshes or fens; and slope wetlands are groundwater discharge driven and support fens 

and wet meadows (Figures 2-10 and 2-11). Mineral soil flats include salt flats.

Table 2-1. Hydrogeomorphic classes of wetlands showing dominant water sources, hydrodynamics, and examples of subclasses (Brinson 1993).

Examples of regional subclass

Hydrogeomorphic class Water source Hydrodynamics Western USA

(geomorphic setting) (dominant) (dominant) Eastern USA and Alaska

Riverine Overbank flow Unidirectional, Bottomland Riparian

from channel horizontal hardwood forests forested wetlands

Depressional Return flow from Vertical Prairie pothole California

groundwater and marshes vernal pools

interflow 

Slope Return flow from Unidirectional, Fens Avalanche

groundwater horizontal chutes

Mineral soil flats Precipitation Vertical Wet pine Large

flatwoods playas 

Organic soil flats Precipitation Vertical Peat bogs; Peat bogs 

portions of 

 Everglades 

Estuarine fringe Overbank flow Bidirectional, Chesapeake Bay San Francisco

from estuary horizontal marshes Bay 

Lacustrine fringe Overbank flow Bidirectional, Great Lakes Flathead Lake

from lake horizontal marshes marshes
26 USDA Forest Service Gen. Tech. Rep. RMRS-GTR-282. 2012

Landscape form and function

Hydrologic and geomorphic processes determine where wetland and riparian ecosystems occur in landscapes, and they control the type of wetland that occurs as well 

as the way it functions. The wetland ecosystem types that occur in the western United 

States (fens, marshes, salt flats, riparian areas, and wet meadows) can be defined by 

their hydrologic and geomorphic regime. Hydrologic processes supporting wetlands 

and riparian areas can be complex. Many wetland complexes have multiple surface 

and/or groundwater flow systems (Winter and others 2001). Wetlands dominated by 

groundwater versus surface water and precipitation may respond differently to natural 

and anthropogenically driven climatic events and variability (Winter 1999). Wetlands 

Figure 2-11. (Top) Aerial photograph of Poison fen, Sierra National Forest, California, showing the directions of groundwater flow from granite 

domes, unforested uplands on east (bottom) and west (left) side of the 

fen. Groundwater discharges into the fen and sheet flows to the south, 

as shown with red arrows. (Bottom) Illustrative cross section along the 

dotted blue line (in top frame) showing the granite domes, hillslope talus 

and alluvium, and groundwater flow and discharge patterns that form the 

sloping Poison fen (green areas) at the toe of slope. 
USDA Forest Service Gen. Tech. Rep. RMRS-GTR-282. 2012 27

that depend primarily on runoff from precipitation for their water supply, such as some 

marshes, may have highly variable water levels, while those dependent on discharge 

from local or regional groundwater flow systems, such as most fens, have the least 

variable water levels (Winter 1999, 2001).

Geomorphic processes drive many disturbances, and landform generation strongly 

influences hydrologic processes and vegetation patterns in all wetland types. For example, riparian landforms are generated by flood-driven sediment erosion and deposition that leads to channel changes and creates a mosaic of landforms such as channels, 

floodplains, point bars, and in-channel islands (Gregory and others 1991) (Figure 2-12). 

These landforms influence the spatial pattern and successional development of riparian vegetation. Riparian plant establishment is linked to the frequency and magnitude 

of flood driven landscape disturbances that produce bare and moist sediment (Baker 

1990, Auble and others 1994, Scott and others 1997, Johnson 2000, Friedman and Lee 

2002, Cooper and others 2003a). For example, braided streams have very high erosion 

and deposition rates and are highly dynamic. Ephemeral streams have only periodic 

flows; little vegetation may occur in the channel or on the floodplain; and the stream 

may wander across the floodplain on a time scale of hours or days. Stream avulsion 

may occur when meander bends erode to shorten a channel length, thereby forming a 

new channel (Figure 2-12), or when a beaver dam pushes flow across the floodplain. 

Disturbance regimes vary as a function of position in the landscape, and the distinctive style, magnitude, frequency, and duration of disturbances may be categorized into 

process domains (Montgomery 1999).

At a landscape scale, glaciers have created the template for wetland formation in many 

regions where glacial till has blocked drainages and created large bodies of unconsolidated 

sediments as well as landforms such as kettle basins and moraine-dammed basins. This 

sediment is recharged with groundwater and may form aquifers with important groundwater flow systems. Glaciers originating in high mountain cirques have created broad, 

U-shaped valleys instead of the V-shaped valleys characteristic of unglaciated areas.

Identifying the water sources and hydrologic regimes of wetlands and riparian areas 

is the first step in understanding the ecological patterns and processes occurring at a site 

of interest. Putting a site into context by identifying its hydrogeomorphic class and its 

process domain can also assist in identifying appropriate reference sites. Such context 

may assist in assessing desired conditions and in identifying sources of stress that may 

be modifying processes that maintain the functions that a wetland or riparian area performs. Furthermore, understanding natural disturbance regimes and distinguishing them 

from human-caused disturbances can help in determining appropriate management 

actions that facilitate desired functions of a site.

Figure 2-12. Processes of lateral channel migration and meander cutoff (modified from Richter 

and Richter 2000). Establishment of riparian cottonwoods and willows occur as a consequence of 

channel migration and point bar formation (green 

areas) as establishment sites are created by 

stream bank erosion on the outside of meander 

bends and the deposition of transported sediments 

on point bars. Channel abandonment and beaver 

pond formation and failure may create large areas 

suitable for riparian plant establishment, allowing 

for the formation of large cohorts of seedlings. 

From Cooper and others (2006) and Westbrook 

and others (2006).
28 USDA Forest Service Gen. Tech. Rep. RMRS-GTR-282. 2012
USDA Forest Service Gen. Tech. Rep. RMRS-GTR-282. 2012 29

Chapter 3: Plant Water Requirements and 

Vegetation Sampling

How plants acquire and use water

Terrestrial plants acquire water to obtain mineral ions and nutrients from the soil, to 

maintain cell turgor pressure and prevent wilting, and to fix carbon through the process 

of photosynthesis. Vascular plants have specialized tissues for water absorption and 

transport, including roots for absorption, xylem vessels (or tracheids) for transport, and 

leaves that regulate water loss. Vascular plant cells have a large central vacuole and 

maintain hydration via water acquisition primarily from the soil. Non-vascular plants, 

such as bryophytes and lichens, lack specialized tissue for water transport, so they must 

directly acquire atmospheric moisture (humidity, dew, and precipitation) or near surface 

soil water. Bryophytes and lichens may periodically be dry or only rarely wet, and their 

water content typically changes seasonally.

A prerequisite for plant photosynthesis is gaseous exchange with the atmosphere 

through specialized openings in leaves called stomata. Stomata allow carbon dioxide 

(CO2) to enter the leaves, providing a carbon source for making carbohydrates. However, 

when stomata open to allow CO2 into the leaf, water may escape into the atmosphere in 

a process called transpiration. The rate of water loss is driven by atmospheric demand 

for water, measured as a vapor pressure deficit (VPD)—the difference between how 

much water a parcel of air can hold at a given temperature and the actual amount of 

water vapor present. VPD drives the energy gradient that pulls water up through the 

plant, creating the soil-plant-atmosphere continuum. The difference between atmospheric 

demand for water and moisture availability to the roots influences the internal water 

status, or water potential, of the plant. Transpiration may create stress on plants if water 

is not available in the soil to replace that which is lost to the atmosphere. The plant 

may respond by regulating (constricting or closing) its stomata, if possible. Prolonged 

water deficit may result in leaf wilting, leaf death, xylem cavitation, branch loss, and, 

ultimately, whole plant death (Rood and others 2000).

Stomatal resistance is the most significant regulation of transpiration for plants that 

closely regulate their stomata because it occurs at the steepest part of the water potential 

gradient, where open stomata expose the interior leaf cells to the potentially desiccating atmosphere. Guard cells adjust the stomatal opening to reduce water loss when soil 

water availability is limited or when very high atmospheric demand makes it impossible 

for a plant’s vascular tissue to provide sufficient water to leaves. Most species undergo 

daily or seasonal stomatal adjustments in response to water availability. Stomata in most 

plants close at night to reduce transpiration when the lack of sunlight reduces the need 

for CO2 exchange for photosynthesis. This stomatal control allows many species to occur in environments that experience seasonal or nearly permanent drought conditions 

or extreme fluctuations in water availability and/or atmospheric conditions. Stomatal 

aperture, transpiration rates per unit leaf area, and photosynthetic rates per unit leaf area 

can all be measured and provide an excellent means of understanding plant functioning.

Vascular plants often have well-developed root systems that allow them to acquire 

water from a range of soil depths and, in some cases, directly from the saturated zone 

(surface or groundwater) or the capillary fringe. Plants that acquire water from the water 

table and its capillary fringe are termed phreatophytes. Vascular plants typically have 
30 USDA Forest Service Gen. Tech. Rep. RMRS-GTR-282. 2012

greater stomatal control than non-vascular plants and dominate a wide range of environments, including deserts, tropical forests, and polar highlands. The only environments 

dominated by non-vascular plants are constantly moist or wet environments such as bogs 

and some fens (peatlands). Sites that are seasonally or periodically wetted, including wet 

meadows, many riparian areas, and all uplands, may have little moss and lichen cover 

because non-vascular plants lack roots and have little ability to regulate their stomata.

Water enters vascular plants primarily through root hairs (Figure 3-1) that have great 

surface area for absorption and high permeability to water. Once water enters the root, it 

flows to vascular tissue where it moves up stems to leaves. Water flows along a pressure 

gradient, which is greatest between the atmosphere and leaf and lowest from soil to root. 

The trunks of woody plants such as trees and shrubs have several tissues, including bark 

and phloem that moves food from photosynthetic to non-photosynthetic portions of the 

plants, and the cambium, where phloem and xylem cells are formed (Figure 3-2). The 

xylem or wood is composed of sapwood that actively transports water and heartwood, 

which provides structure but little water conduction. Most xylem tissue is composed of 

dead hollow cells with lignified walls.

Figure 3-1. Whole tree showing a cross section of leaf with stomata (c), and a cross 

section of a root showing rootlets and root cells (b).
USDA Forest Service Gen. Tech. Rep. RMRS-GTR-282. 2012 31

Many species of riparian plants require access to a permanent or seasonal water supply 

and are intolerant of low internal water potentials (e.g., high water stress). Whereas most 

phreatophytes are thought to maintain contact with the vadose zone (unsaturated zone 

of capillary rise above the water table), even during periods of low flow, other species 

may have an affinity for fine textured substrates with high water holding capacity or 

may be able to utilize water at low soil water pressure potentials (Naumburg and others 

2005). Some riparian species can utilize different water sources over the course of the 

season, with various proportions of transpired water coming from groundwater versus 

soil water depending on relative availability (Busch and Smith 1995, Smith and others 1998). Species that can acquire water from multiple sources may be better adapted 

to extended periods of low flow caused by drought, groundwater pumping, and water 

extraction (Stromberg and others 2007a).

Flow permanence (length of time with surface flow) and depth to groundwater, 

accounted for much of the variability in dominance by native or exotic species along a 

riparian hydrologic gradient in Arizona, USA (Lite and Stromberg 2005). Sites that had 

surface flow for 76 percent of the time, groundwater depths of <2.6 m, and variability of 

groundwater depth of <0.5 m tended to be dominated by native forest species. Decreasing flow permanence and increasing depth and variability of groundwater beyond these 

thresholds resulted in an increasing probability that native-dominated woodlands could 

shift to exotic shrublands, leading to changes in stand-level vegetation characteristics 

Figure 3-2. Cross section of typical tree showing layers of 

woody tissue. The arrow at (A) points to the outer layer, which 

is bark. Inside the bark in succession are the phloem, cambium, 

sapwood, and heartwood shown at (B). The sapwood is the 

main water conducting tissue in the tree and contains xylem 

vessels. Large pores are shown in (C).
32 USDA Forest Service Gen. Tech. Rep. RMRS-GTR-282. 2012

(e.g., canopy height and vegetation volume). Along a depth to water table gradient, 

non-riparian phreatophytes, such as Sarcobatus vermiculatus (greasewood), also vary 

their use of soil and groundwater (Chimner and Cooper 2004).

When subjected to prolonged periods of drought, even the most drought-tolerant riparian 

plants are vulnerable to water stress, wilting, leaf death and stem dieback, and, ultimately, 

mortality (Tyree and others 1994, Scott and others 1999). As desiccation occurs, species 

vary greatly in their ability to regulate their water pressure potential (through stomatal 

closure or other leaf morphologic traits) (Pockman and Sperry 2000). Loss of leaves 

through leaf abscission and/or xylem cavitation and branch death (“drought pruning”), 

reduces the total plant water requirements and may actually save the individual at the 

cost of some portion of the canopy (Tyree and others 1994). For some species, such 

as Populus deltoides, there is an identifiable threshold of percent leaf and branch loss 

before mortality is likely (Scott and others 1999, Cooper and others 2003b).

Measuring plant water relations

Stomatal conductance

Measures of stomatal conductance are important for understanding transpiration 

rates and water use efficiency. Furthermore, the diurnal and seasonal patterns of plant 

adjustment to changes in water availability provide key information for understanding plant functioning. For example, the diurnal pattern of stomatal conductance (gs) is 

important for understanding how plants function during the day and recover at night 

(Oren and Sperry 1999).

Leaf stomatal conductance and transpiration rates can be measured with a porometer 

or portable photosynthesis system (Figures 3-3A and B). This instrument measures the 

rate of dry air needed to maintain a constant relative humidity inside a small chamber 

enclosing a transpiring leaf. Photosynthesis systems utilize one or more infra-red gas 

analyzers that measure the CO2 and H2O vapor concentrations within the leaf. Porometer 

measurements are made on leaves in situ (Figure 3-3A). Ladders or scaffolding may be 

needed to access suitable leaves. Leaves or twigs that hold the set of leaves for measurement should be marked, making repeat measures over the day or season possible. Data 

Figure 3-3. The measurement of transpiration and stomatal conductance of a Populus spp. tree using a porometer (Li-COR LI1600 or similar instrument). 

A B
USDA Forest Service Gen. Tech. Rep. RMRS-GTR-282. 2012 33

depicted in Figure 3-4 are from an experiment where Populus spp. trees were irrigated 

and compared with unwatered trees. Plants opened their stomata at dawn and reached 

maximum gs by early to mid morning (Figure 3-4). By late morning, unwatered plants 

were adjusting their stomata to reduce transpiration, while watered plants were not. On 

a seasonal basis, stomatal conductance may increase, however morning gs is higher than 

afternoon gs throughout the summer, indicating that afternoon stomatal control occurred 

due to limited water availability and a desiccating summer environment.

Figure 3-4. Morning and afternoon stomatal conductance (left panels) and diurnal patterns of stomatal conductance of Populus spp. trees using a porometer. Irrigated Populus are indicated with black filled symbols; 

unwatered Populus are unfilled symbols at sites NR1, NR2, R1C, and R2C.

Xylem pressure potential

Water is a polar molecule. As a result, water molecules adhere to each other and to 

the vessel walls of the xylem. Transpiration pulls the chain of water molecules up the 

plant, but when water is transpired faster than it can be replaced in the xylem, tension 

on the chain of water molecules in the xylem increases and is exerted through the entire 

plant. When a twig or leaf petiole and its xylem is severed from the parent plant, the 

pressure necessary to force water back to the cut surface is equivalent to the negative 

pressure (internal water stress) in the xylem prior to cutting. A Scholander-type pressure chamber can be used to measure this pressure and provides an excellent measure 

of tension within the xylem. A leaf with a petiole or twig is cut and placed upside down 

into the chamber with the cut end protruding (Figures 3-5). Pressure is increased in the 

chamber and the cut end is observed with a magnifying glass. When the pressure exerted 

equals the tension at which water is held within the xylem, water flows back through 

the xylem and appears on the cut end. When water first appears, this xylem pressure 

potential is recorded and represented with the symbol Ψxp.

Differences in hydraulic architecture make some tree species more sensitive to water 

stress than others (Sperry 1995, 2000). Vulnerability curves have been developed for a 

number of species to quantify their loss of hydraulic conductivity along a gradient of 

xylem pressures (Tyree and Sperry 1989). For example, Tyree and others (1994) produced vulnerability curves for Populus spp. to show loss of water conducting ability 

and the pressures at which partial or complete loss of xylem conductance occur (Blake 

and others 1996).
34 USDA Forest Service Gen. Tech. Rep. RMRS-GTR-282. 2012

Figure 3-5. Left: cross section of pressure bomb showing cut leaf (or twig) inside the chamber with the cut end protruding through 

the rubber stopper and chamber top. The exhaust valve is closed and pressure increased until water flows back through the xylem and is expressed on the cut leaf or twig surface (top right). The researcher carefully watches the cut surface as the pressure 

increases, recording the pressure at which the water emerges (bottom right). 

Measuring transpiration rates

Transpiration is an important determinant of leaf energy balance and plant water 

status (Pearcy and others 1989). Most studies of plant-water relations involve measurement of leaf transpiration and leaf conductance to water vapor as they enable an 

investigator to determine plant water use efficiency. Transpiration can be measured at 

the scale of the leaf, individual plant, or a meadow, forest, or stand using a variety of 

techniques. These measurements require specialized equipment and expert knowledge 

of the techniques and theory behind them, so clear objectives should be made in the 

study planning phase. Brief explanations of several techniques follow. For more detailed 

explanations, theory, and instructions, please refer to plant physiology textbooks (e.g., 

Chapters 3, 8, 9, 11, and 13 of Pearcy and others 1998) and/or instruction manuals for 

specific measurement devices.

Leaf-level transpiration is typically measured as previously described. Leaf-level water 

conductance (water exiting a leaf through stomata) is often derived from transpiration 

rates measured in chambers. A number of companies make instruments for measuring 

leaf-level water conductance in the field, including LI-COR (www.licor.com), PP systems 

(www.ppsystems.com), and Decagon (www.decagon.com). Leaf-level measurements 

may be made on multiple leaves on the individual of interest over the course of a day 

(or season) to better understand the physiological response of the plant to changes in air 

temperature, humidity, precipitation events, soil moisture, water levels, and streamflow.
USDA Forest Service Gen. Tech. Rep. RMRS-GTR-282. 2012 35

Whole plant-level transpiration rates may be analyzed using heat as a tracer to 

measure water flux through the stems of woody plants. One method for measurement 

of sap (water) flux through trees uses pairs of probes inserted through the sapwood as 

shown in Figures 3-6A, B, and C. The bottom probe measures ambient temperature of 

the wood. The top probe measures temperature and also has a heating element that produces a constant flow of heat. Water conducts heat and transports it up and away from 

the heating element. The difference in temperature between the two probes is measured. 

Higher temperature differences between the two probes indicates a slow flow of water 

up the tree, while a smaller difference indicates a higher rate of flow. Water movement 

up the tree is calculated as sapwood cross sectional area multiplied by the rate of sap 

flux. These data can be calculated as daily or annual flux. The thickness of sapwood 

for a tree (light area in the cross section shown in Figure 3-6A) can be determined by 

measuring sapwood thickness with increment cores (Figure 3-6B), or other methods, 

from around the tree bole or through measurement from a cross section of the stem. 

A

C D

B

Figure 3-6. Sap flow methods can be used to calculate flow rates of water up the sapwood of tree boles. Knowledge of the sapwood 

thickness and area (A and B) is determined with cores, or cross sections, and flow rates are determined with pairs of probes (C) or 

bands. Sap flow can provide informative (D) diurnal patterns of water use in trees. The Granier 20 and TPD30 are two different 

types of sap flow probes, and a number of methods and systems are available for sap flow studies.
36 USDA Forest Service Gen. Tech. Rep. RMRS-GTR-282. 2012

However, there are many new approaches for measuring sap flux and many different 

probe types are available, each of which may be most appropriate for a particular tree 

species or question. Since differentiation of active xylem can be challenging for some 

species, laboratory analyses are required and probes can be calibrated in the lab following the procedures of Steppe and others (2010). Sap flux technology is complex 

and a thorough understanding of the methods, calibration, and analysis of these data 

is required to successfully utilize these techniques. Many studies have shown that the 

original Granier sap flow equations are not robust for all species, and new ideas about 

how to measure sap flow are being published (Clearwater and others 1999, Taneda and 

Sperry 2008, Bush and others 2010, Hubbard and others 2010). Sap flux over time may 

be plotted and compared across treatments, through space, and over time (Figure 3-6D).

Identifying plant water sources

Many wetland and riparian plants utilize groundwater as well as soil water that 

is recharged by precipitation. Although many wetland and riparian plant species are 

phreatophytes, they may primarily utilize soil water recharged by precipitation. Some 

plants are adept at taking advantage of groundwater and soil water at different times of 

the year (Busch and Smith 1995). Understanding the water sources used by plants is 

critical to understanding plants’ link to, and degree of dependency upon, groundwater. 

Relationships between incremental growth, branch growth, productivity, and canopy 

condition and hydrologic variables (such as streamflow) can provide strong clues about 

linkages between fitness and various water sources to plants (Stromberg and Patten 1991, 

Willms and others 1998). In determining water sources and needs for riparian vegetation, 

it is important to understand the relationship between plant age or developmental stage, 

root morphology, and water acquisition. Vulnerability to water stress may decline as a 

function of age or developmental stage for many species. As a result, it is important to 

understand how many years it takes for woody plant seedlings or saplings to develop 

roots deep enough to acquire groundwater in the summer, or to determine the proportion 

of rain-recharged soil water that typical phreatophytes utilize.

Stable isotope ratios of oxygen (O) and hydrogen (H) can be used as tracers to identify 

water sources. Water is composed of O and H, and both elements occur in elemental and 

isotopic forms. O has an atomic number (protons) of 8 and an atomic mass (neutrons + 

protons) of 16. However, its most common isotope has two extra neutrons, and while 

its atomic number remains identical, its atomic mass is 18. H has an atomic number and 

atomic mass of 1; however, its most common isotope deuterium (D) has an atomic mass 

of 2. If a basin of water is set in the sun, water molecules with D or 18O evaporate more 

slowly (due to their greater atomic mass) than do water molecules with H or 16O, leading 

to an enrichment of water in D and 18O. Evaporative enrichment occurs in most soils 

that are recharged by precipitation. The ratio of D to H (expressed as δD), or 18O/16O 

(expressed as δ18O) can be measured with a mass spectrometer. If δD or δ18O is distinct 

in soil water as compared to groundwater, then the water source used by plants can be 

identified by comparing plant sap extracted from suberized stems (those with welldeveloped bark) with potential water sources. Water is extracted from soil samples and 

plant stems using a process called cryogenic distillation, and groundwater is collected 

by pumping water from monitoring wells. The isotope ratio is then calculated relative 

to a standard water source using the following equation:

δD (‰) = [(D/H)sample/(D/H)standard -1] x 1000

The typical standard is Standard Mean Ocean Water (SMOW).
USDA Forest Service Gen. Tech. Rep. RMRS-GTR-282. 2012 37

Cooper and others (1999) used stable isotope methods to determine that Populus

seedlings along the Yampa River were using primarily soil water during the summer 

until they were at least two to three years old (Figure 3-7). Older plants used primarily 

groundwater, although much older plants (>90 years old) used both soil and groundwater. This investigation identified that seedlings were not phreatophytes and that their 

survival was not dependent upon growing a taproot fast enough to remain connected 

to the declining summer water table. Using stable isotopes, Busch and others (1992) 

found that a group of native riparian woody species (including Populus spp. and Salix 

spp.) were obligate phreatophytes along an arid land river but that a non-native shrub 

utilized both soil and groundwater during the growing season.

Stable isotopes of carbon (C) can also be used for analyzing plant-water relations 

(Jackson and others 1993). The isotopic ratio of 13C to 12C in plant tissue is less than 

the isotopic ratio of 13C to 12C in the atmosphere, indicating that plants discriminate 

against 13C during photosynthesis. Variation in discrimination against 13C is due to both 

stomatal limitations and enzymatic processes. Theoretical and empirical studies have 

demonstrated that carbon isotope discrimination is highly correlated with plant 

water use efficiency, providing an integrated measure of water use efficiency (a 

measure of carbon fixation for an amount of water transpired). Measurement of 

carbon isotope discrimination is relatively easy to carry out because carbon used 

to build plant tissue reflects the amount of discrimination present when the tissue 

was constructed. Samples are easily collected in the field for later processing in a 

laboratory. Moreover, in woody plants, carbon isotope discrimination can be determined from annual ring samples, providing a historical analysis of plant response to 

environmental conditions. Using carbon isotope discrimination to determine water 

use efficiency, Busch and Smith (1995) found that a non-native riparian species had 

higher water use efficiency than several native shrubs. This higher water use efficiency 

Figure 3-7. Sap water δD of groundwater (water); plants of 90+, 20-, 

8-, 4-, 2-, and 1-year old cottonwoods; and soil water, illustrating that 

younger plants used primarily soil water.
38 USDA Forest Service Gen. Tech. Rep. RMRS-GTR-282. 2012

provided an explanation for the differential survival of non-native versus native species 

along a flow altered river. Studies have found that depleted groundwater and altered 

timing and magnitude of flow may cause a shift in riparian areas from those dominated 

by native obligate phreatophytes to those dominated by non-native species (Stromberg 

and others 2007b, Merritt and Poff 2010).

Hydrogen isotope composition of cellulose from tree rings may also be used as an 

index of historical water source use by riparian trees (Alstad and others 2008). Analysis 

of cellulose D provides a time-integrated signal of changes in water sources to woody 

riparian plant species (currently only about a decade into the past) and may provide 

indications of switches in water use from one source to another or may provide insight 

into reductions in water availability from an existing source. For example, analysis of 

cellulose D from tree ring tissue may provide insight into a switch in water use from 

groundwater to soil or atmospheric water following groundwater decline or streamflow 

alteration.

Sampling of tissue and water for stable isotope analysis involves collection, proper 

handling, and timely delivery of samples to a laboratory for analysis using an isotope ratio 

mass spectrometer. Collection of water samples from groundwater wells, rain gauges, 

stream water, and/or soil water as well as water in plant tissues may be necessary for 

determination of isotopic composition, depending on the objectives of the study. Water 

samples should be immediately sealed in filled glass vials to avoid any evaporation of 

water from plant tissues. Leaves, stems, and xylem water from tissue samples have commonly been used in stable isotope studies and may be collected by clipping or pruning 

the desired portion of the plant. Samples should be packaged and chilled (preferably 

frozen) and shipped immediately to the laboratory to avoid fractionation and loss of organic material. For a more thorough discussion, refer to Ehleringer and Osmond (1989).

Laboratories that perform isotopic analysis on tissue and water samples include:

University of Colorado: http://instaar.colorado.edu/sil/about/index.php;

University of California, Davis: http://stableisotopefacility.ucdavis.edu/;

Northern Arizona University: http://www.mpcer.nau.edu/isotopelab/pricing.html;

and many private laboratories.

Plant ages and growth

A critical issue in riparian management in western North America is Populus and/or 

Salix establishment and survival. Since rivers have varying interannual flow regimes, 

knowing the exact year woody plants establish allows researchers to link plant 

establishment to a particular year’s flow regime. In addition, determining the age 

structure of woody plant populations is critical for helping to understand the years in 

which plant establishment success has been high, the hydrologic conditions associated with establishment and survival, and possible hydrologic or climatic bottlenecks 

in survival of such species. The determination can also allow scientists to suggest flows 

for environmental maintenance or restoration.

When the seed of a woody plant such as Populus germinates, its cotyledon grows 

a stem and a root. This germination point, which occurs at the soil surface (Figures 3-8 

and 3-9), is termed the root crown or root collar. As the plant grows and develops 

woody tissue, stem tissue develops a pith. Stem tissue can always be identified in cross 

section by the presence of pith (even following burial), while root tissue lacks a pith. 
USDA Forest Service Gen. Tech. Rep. RMRS-GTR-282. 2012 39

Figure 3-8. Diagram of young tree showing the 

soil surface and the stem tissue above and root 

below that point. The stem contains a pith and 

growth rings reflecting each year’s growth. The 

point where the pith originates is the root crown.

Figure 3-9. Photograph of an excavated Tamarix. The 

sanded Tamarix spp. slab at bottom contains a pith (the light 

center), indicating that it is stem tissue. Root tissue lacks a 

pith. Excavated Populus bottom right.
40 USDA Forest Service Gen. Tech. Rep. RMRS-GTR-282. 2012

Because stems grow upward and add successive layers of wood in a ring-like pattern, 

the younger stem areas contain fewer rings than the root crown. While an increment core 

collected above the ground surface from a tree bole can be used to obtain a general idea 

of tree age, it cannot be used to determine the year in which riparian tree establishment 

occurred (Figure 3-10). Along fluvially active streams, the stems of individuals may be 

sheared off or buried by sediment, causing the germination surface of the resprouted 

plant to be buried and the aboveground portion of the plant not to reflect the true age 

of the individual. When attempting to determine establishment age of such individuals, the plant must be excavated to find the root crown, and the age at the root crown 

must be determined through examining growth rings. For shrubs, or browsed plants, 

it should be assumed that no stem contains the full set of rings, and excavation of the 

plant to identify the root crown is necessary. Through excavation of the roots of willow, cottonwood, or Tamarix (Figure 3-9), root morphology can be characterized and 

the taproot can be preliminarily identified. Then, cross sections of the stem should be 

collected, and the root crown can be identified. The root crown is located between the 

cross section that has pith (stem tissue) and the cross section that does not contain pith 

(root tissue). If a cross section has pith on the top and no pith on the bottom, the root 

crown (and germination surface) is contained in the cross section.

This section bridges the root crown and should contain the full complement of annual rings. If plants are deeply buried by fluvial sediments, stem tissue becomes root 

tissue, which can be very porous and, in some cases, difficult or impossible to interpret. 

In addition, trees along some intermittent streams or following drought may produce 

false rings (more than one per year). In extreme cases, rings may be absent. Therefore, 

it is important to cross date ring widths among trees and relate them to known climate 

and hydrologic events.

In addition to simple ring counts to age trees, cores extracted from aboveground 

stems may also be analyzed to measure the width of incremental (annual) growth rings 

and to quantify tree growth rates. Tree cores may be measured precisely using a binocular microscope. Ring width may be digitized using specialized equipment such as a 

Velmex TA Unislide measuring system with an ACU-Rite linear encoder and QC1100 

digital readout device (Velmex, Inc., Bloomfield, New York). Ring-reading software 

Figure 3-10. An increment borer may be used to collect cores of trees 

and shrubs. Cores are then dried, mounted onto a board, sanded, and 

polished. Rings are counted or ring widths are measured to determine age 

or growth rate, respectively. 
USDA Forest Service Gen. Tech. Rep. RMRS-GTR-282. 2012 41

includes Measure J2X, Version 3.1 (Project J2X, Voortech Consulting, Holderness, 

New Hampshire).

Another growth measure that is tightly coupled with water availability in arid and 

semiarid riparian systems is annual branch growth. Measuring the increments between 

annual bud scale scars provides a measure of growth in the past growing seasons. An 

annual branch growth measurement may be sensitive (in some cases, more so than incremental ring growth) to the effects of changes in groundwater levels (e.g., groundwater 

pumping; Scott and others 1999) and to variations in river flow regime (Willms and others 1998). Branch growth increments may provide an accurate record of environmental 

favorability for recent growth over a period of one to two decades. Close correlations 

between branch growth and stream flow indicate that water limits growth of riparian 

plants and that such plants obtain their water from a source linked to the stream, such 

as the riparian water table (Willms and others 1998). Analyses of branch increments 

provide a management tool for determining instream flow needs for riparian trees and 

for analyzing impacts of stream flow alterations due to river damming, water diversion, 

and groundwater pumping.

Patterns of plant dieback

The outward signs of water stress in plants may include discoloration, wilting, and/or 

dead leaves or branches. Woody plant stems or root systems may dieback due to drought, 

water management actions, disease, and other factors. Understanding the patterns of 

dieback assists in linking plant health to environmental and management actions.

Other plant morphological measures that can be useful in assessing riparian and 

wetland health and tracking changes in condition through time are: vegetation volume, 

canopy cover, canopy height, woody plant stem density, and woody plant basal area 

(Stromberg and Patten 1991, 1996; Lite and Stromberg 2005). Vegetation volume may 

be measured using the vertical line intercept method at a number of points per plot 

(Mills and others 1991). Maximum canopy height within plots may be measured using 

either a vertical measuring pole or a clinometer. Canopy cover may be measured using 

a spherical densiometer at several points (plot corners and center) per plot or by using 

a densitometer with point or line intercept layout (Elzinga and others 2001).

Percent of potential canopy can be used to assess damage caused by water stress associated with leaf death and abscission, water stress and cavitation, and branch dieback 

(Scott and others 1999) (Figure 3-11). Potential canopy should be estimated as a visual 

determination of percentage of live canopy relative to potential crown volume (i.e., 

extent of all branches; Scott and others 1999) for all woody species. Crown dieback has 

been associated with increased risk of mortality the year following dieback in riparian 

trees (Scott and others 1999).

Root density and biomass with depth can be quantified from samples collected in pits 

or cores to compare areas affected by water management activities to reference areas. 

Williams and Cooper (2005) found that cottonwood root density and biomass was much 

higher for the unregulated Yampa River, which still has overbank flooding compared 

with the regulated Green River which rarely floods.

Dead stems can also be collected and their ring patterns can be compared with other 

live trees to identify the year of death (Figure 3-11). This requires the development of 

a tree ring chronology from healthy stems using collected increment cores. Analysis 

of tree populations in a holistic manner (evaluating their physiological functioning), 

including analysis of stomatal conductance and/or xylem pressure, age structure of 

stands, and dieback patterns of roots or stems, informs researchers on tree- and standlevel condition and the effects of long-term management activities on the persistence 

of riparian vegetation (Figure 3-11).
42 USDA Forest Service Gen. Tech. Rep. RMRS-GTR-282. 2012

Figure 3-11. Individual trees, such as the cottonwood shown here, can yield a wide range of data and information, including 

physiological measures (top right), increment cores to illustrate overall growth rates and patterns of stem dieback (center 

image), root distribution and density (top left), and root crown age (bottom left). 
USDA Forest Service Gen. Tech. Rep. RMRS-GTR-282. 2012 43

Vegetation sampling

Vegetation is sampled to characterize the current composition of plants occurring 

on a site and to develop a baseline for future vegetation analyses. A large number of 

methods have been proposed and used for vegetation analysis; for an overview of this 

topic, please consult a textbook (e.g., Mueller-Dombois and Ellenberg 1975, Elzinga 

and others 2001). Two of the most popular methods are plot-based and transect-based 

sampling. Each method has its strengths and weaknesses and can be used for distinct 

purposes. Plots can be centered around groundwater monitoring wells to characterize 

the composition of homogenous stands or patches of vegetation in different hydrologic 

settings, or they can be around monitoring wells with different long-term water table 

depths. Transects can be used to sample vegetation along environmental gradients or 

in large stands where a broad sample area is desired (Figure 3-12). It is critical that 

sample size of plots meets the criteria for minimal area, that is, the minimal sample area 

that adequately represents the community composition. The sum of sample area along 

transects should also meet this minimal area criterion.

Figure 3-12. A tape measure laid out to measure vegetation 

using the line intercept method, a transect-based method.
44 USDA Forest Service Gen. Tech. Rep. RMRS-GTR-282. 2012

Some sample procedures use a single plot, while others have nested plots or nested 

plots placed along transects. Different plot sizes are used to sample herbaceous and 

woody plants. For example, 1x2 m plots are used to sample the composition and cover 

of herbaceous vegetation and two- to four-year old saplings (woody species), and 2x10 

m plots are used to sample shrubs and trees (for estimation of shrub cover, tree stem 

density, and tree diameter). Along one transect, an example of plot layout is: 1x2 m plots 

located on the downstream side of the transect line/meter tape (the landward upstream 

corner of the plot on the selected distance along the tape). Each 2x10 m plot would have 

its origin (landward upstream corner) on the same point as the herbaceous plots. Each 

nested herbaceous and shrub-tree plot would correspond to its associated distance along 

one transect, with the exception of the belt transects nearest the lowest extent of vegetation, in which case each shrub-tree plot will be associated with two herbaceous plots.

If a single plot is used, the plot should be within a homogenous stand of vegetation. A 

list should be made of all plant species that are present, including bryophytes and other 

taxa if possible, and the absolute canopy cover of each species should be estimated.

Modified Braun-Blanquet cover classes are suitable for visually estimated vegetative 

cover in plots: cover class 1 = <1 percent canopy cover, 2 = 1 to 5 percent, 3 = 5 to 25 

percent, 4 = 25 to 50 percent, 5 = 50 to 75 percent, and 6 = 75 to 100 percent. Within 

each plot, cover of each vascular species and ground cover feature (water, bare ground, 

litter, bryophytes, rock, and large wood pieces) should be recorded. If nested plots are 

used, or transects with different sized plots, the smaller plots are used to record the 

cover and abundance of herbaceous plants, bryophytes, shrubs, and young trees, and 

larger plots are used for trees.

Woody plant recruitment

The presence of woody species saplings should be recorded (by species) along 

transects when the stem or canopy of a two- to four-year old individual intersects the 

transect. Age may be determined by taking a cross section of several individuals off of 

the transect and counting annual growth rings. The presence of two- to four-year old 

individuals is considered evidence of recruitment, and the frequency of recruitment 

provides an important and sensitive measure of the recruitment success along a reach 

(Merritt and Poff 2010). Younger individuals (<two years) are less informative because 

they may be abundant annually but mortality is often quite high on most years (e.g., 

seedlings are not a good indicator of successful recruitment; Cooper and others 1999). 

Care should be taken to distinguish between saplings resulting from root sprouting and 

those germinated from seed; this should be recorded when distinguishable.

Distance along the transect where the regenerate occurs should be recorded for each 

individual intersecting the transect. This will provide a count of regenerates by fluvial 

feature for the entire reach and a calculation of number of saplings per meter.

Size-class structure

Within plots, the number of small (<2 cm diameter at breast height [DBH]) tree stems 

should be counted and all tree stems ≥2 cm DBH should be measured. It should be 

noted if tree stems occur in a cluster (e.g., they are sprouting from a larger tree). If a 

tree occurs near the edge of the plot, it should be measured if >50 percent of the tree 

stem is within the plot boundary. If stem density is relatively uniform in the plot and of 

high density, stems can be subsampled by counting the number of stems in a smaller 

measured area. If a tree or shrub occurs near the edge of the plot, it should be measured 

if >50 percent of the shrub or tree stems are inside the plot boundary. Histograms of sizeclass structure distributions may be constructed from gathered data and comparisons of 

distributions, central tendency (e.g., mean or median), variation (e.g., standard deviation 
USDA Forest Service Gen. Tech. Rep. RMRS-GTR-282. 2012 45

and coefficient of variation) can be made between treatments, effected and unaffected 

reaches, etc. Furthermore, basal area can be calculated and summarized by species.

Condition

Shrub and tree health can be assessed visually through a simple evaluation of leaf 

condition (Cooper and others 2003b; Chapter 6: Case Study II). Wilting from prolonged 

water stress can result in leaf discoloration and partial or complete leaf death. Record 

the collective status of the canopy of shrubs and trees by species within the shrub-tree 

plots using the following categories:

•	 critically stressed = major leaf death and/or branch dieback (>50 percent of canopy 

volume affected);

•	 significantly stressed = prominent leaf death and/or branch dieback (20 to 50 percent of canopy volume affected);

•	 stressed = minimal leaf death and/or branch dieback (<20 percent of canopy 

volume affected);

•	 normal = little or no sign of leaf water stress/no water stress-related leaf death;

•	 vigorous = no sign of leaf water stress/very healthy looking canopy.

Using this ordinal scale, frequency of categories may be statistically compared between sites or reaches. Crown dieback has also been associated with increased risk of 

mortality in riparian trees (Scott and others 1999). Percent of potential canopy can be 

used to assess damage caused by water stress associated with leaf death and abscission, water stress and cavitation, and branch dieback (Scott and others 1999). Potential 

canopy should be estimated as a visual determination of percentage of live canopy 

relative to potential crown volume (i.e., extent of all branches; Scott and others 1999) 

for all woody species (Figure 3-13).

Figure 3-13. Visual estimation of 

percent live canopy as a measure of 

condition. The observer visualizes a 

full canopy and then estimates the percentage of that maximum area that is 

occupied by canopy (to the nearest 5%).
46 USDA Forest Service Gen. Tech. Rep. RMRS-GTR-282. 2012
USDA Forest Service Gen. Tech. Rep. RMRS-GTR-282. 2012 47

Chapter 4: Measurement of Surface Water 

and Groundwater Levels

Many wetland and riparian areas are supported by both surface and groundwater, 

which should be considered a single resource (Winter 1999). Surface water recharges 

groundwater in some areas and groundwater discharges to the surface in other situations. 

Riparian ecosystems occur along streams and are hydrologically and geomorphically 

driven by surface waters, which supply shallow alluvial groundwater and influence 

turnover between surface and groundwater (also referred to as hyporheic exchange). 

Thus, stream flow, stream stage, stream dynamics, overbank flooding, and groundwater 

recharge or bank storage are interrelated functions. The measurement of these components is key to understanding the processes supporting these systems. The hydrologic 

processes supporting each wetland or riparian type should be carefully considered before 

designing a hydrologic monitoring program.

Fens are largely groundwater driven, and the analysis of water table depth relative 

to the soil surface, vertical gradients of groundwater flow, and as surface water inflows 

and outflows (if any exist) are critical components to measure in these systems. Fens 

also have little mineral sediment deposition; therefore, monitoring surface sediment 

deposition may be critical.

Wet meadows are also largely groundwater fed but may have surface water inflows 

or outflows as well. The critical features to analyze are the duration of the water table 

near the soil surface, duration of soil drought, and mineral sediment deposition rates. 

Measurement of soil redox potential over the course of a season or several seasons in 

wet meadows (and other wetland types) may provide insight into the range of variability 

typical of these systems and how hydrological alteration might change such systems.

Salt flats may be supported by surface water ponding on a relatively impermeable 

mineral sediment layer or shallow groundwater that supports a capillary fringe that at 

least seasonally reaches the soil surface. Measuring surface water inflows and outflows 

as well as pond water depth and duration is critical for surface water-supported salt flats.

Marshes are basins filled largely by shallow surface water, or wetlands fringing larger 

and deeper lakes. Measuring surface water inflows, outflows, and the depth, duration, 

and extent of ponded water as well as the rate of groundwater recharge is critical for 

understanding marsh functioning and the distribution of plant species.

These sites could be instrumented to investigate the connection between surface water 

and groundwater. Such instruments include piezometers (measure the hydraulic head 

above a well opening within confining layers), groundwater monitoring wells (measure 

water table level of unconfined water surface at atmospheric pressure), and staff gauges 

(measure surface water level) (Figure 4-1). Measurement of soil moisture and/or redox 

potential, particularly in wetter areas, may also provide important information about 

these wetlands.

Spatial scale of analysis and monitoring

The spatial scale of analysis should be determined in the planning stages, before 

installation of any instruments, and should include the area that may provide water, 

sediment, or other inputs to the study site. The distribution of measuring points and 

monitoring instruments should be preliminarily determined from analysis of air photos. 
48 USDA Forest Service Gen. Tech. Rep. RMRS-GTR-282. 2012

Single wells only provide information about depth to water table (and its variation) 

below a single point. Installing grids or arrays of wells, peizometers, and staff gauges 

that cover the extent of the area of interest can enable the development of two- and 

three-dimensional water surface profiles. Surface waters should be measured at points 

of inflow and outflow to the study area, and water stage should be measured in areas 

where groundwater would be measured along transects, grids, or in plant communities 

that are of special interest. Groundwater should be measured in locations thought to 

have significant inflows to the wetland, within communities of special interest, near 

streams, and, in some instances, under streams.

Temporal scale of analysis and monitoring

The temporal scale of analysis should be determined in advance and be based upon 

the questions being addressed. For questions regarding the influence of precipitation or 

flow events on river stage or water tables or daily evapotranspiration-driven water table 

changes, data loggers associated with groundwater monitoring wells and staff gauges 

may provide information at the correct temporal scale. The most suitable temporal scale 

may vary from minutes or hours to weeks or months. Frequent data collection is needed 

to answer questions regarding seasonal duration of the water table within the root zone 

of plants. In remote areas, it may be difficult to visit the site regularly and make manual 

measurements. Instead, an automated measurement system that allows the collection of 

complete data sets can be installed with one or two visits made annually.

Figure 4-1. Connections between surface and groundwater may be measured using nested piezometers (which 

can indicate vertical flow within confined aquifers), groundwater monitoring wells (which measure water table 

level at atmospheric pressure), and staff gauges (which measure water surface level in a stream or water body).
USDA Forest Service Gen. Tech. Rep. RMRS-GTR-282. 2012 49

Approaches for measuring surface water and groundwater

Surface water

Surface water, including stream flow and pond or lake levels, is measured using 

staff gauges, weirs, and/or flumes. The relative or absolute level (elevation) of the 

water surface (also called stage) is measured using a staff gauge or staff plate, which 

is a measuring device anchored to the stream or lake bottom on which water level is 

measured. Regular measures of stage relative to the stream bottom, pond bottom, some 

datum below the ground surface (e.g., to keep all values positive), or a permanent reference benchmark can be made by hand and recorded in a field book. Water depth, stage, 

or elevation can be plotted using a simple line graph to show the water height in meters 

or feet above the datum, pond, or stream bottom (Figure 4-2). Regular measures (daily, 

weekly, or biweekly) are best for understanding the overall annual change in stage. For 

snowmelt-driven streams, there may be considerable daily stage change in spring and 

early summer due to the diurnal pattern of snowmelt. Measurements should be made 

at (or throughout) the same time of day, so that relative seasonal changes can be addressed. Manual measures would not provide a measure of instantaneous daily peak 

stage because the exact timing of peak flow and stage is unknown. In addition, some 

streams and ponds have stage rises during the summer that are driven by rain events, 

and manual measures will likely miss the exact timing and total stage change produced 

by these events.

If discharge can be measured simultaneously with stage, a rating curve relating water 

stage to discharge can be constructed (Figure 4-3A). This rating curve can then be used 

to calculate flow from stage height or vice versa (Figure 4-3B).

Continuous data on river or pond stage provide much more information on the maximum peak river stage, the duration of peak stage, whether multiple peaks occur, and 

the rate of stage change. However, since most streamflow gauge data are published as 

discharge, stage data may be absent or not specific to a study area. Most U.S. Geological 

Survey (USGS) and state gauge sites measure stage and use a rating curve constructed 

from a subset of field-measured stage and discharge to estimate stream discharge. During 2000, the Tuolumne River (Figure 4-4) had three major periods of high flow, one 

in mid-May, a second in early June, and a third in late June.

Figure 4-2. Stage (height) of water column over time based upon a series 

of manual measures. 
50 USDA Forest Service Gen. Tech. Rep. RMRS-GTR-282. 2012

Figure 4-3. Rating curve for Tuolumne River at Highway 120 in 

Yosemite National Park, California, and stream flow calculated 

using river stage for water years 2002 to 2006. Portions of the 

discharge lines in the rating curve (A) indicate results from 

least squares fit alternating between stage or discharge as 

the predictor. Both yield the same equation: Q = 31(h-1.9)2.3, 

where h is the staff gage reading in feet. Solid black dots 

on the hydrograph (B) indicate measured discharge used to 

construct and validate the rating curve. 

Figure 4-4. Continuous discharge for the Tuolumne 

River near Highway 120 in Yosemite National Park, 

California, from April 2000 through early August 2000. 

Streamflow peaked in early June followed by a coldspell and then returned to high flow in late June, which 

was punctuated by afternoon thundershowers that 

caused small stage rises.
USDA Forest Service Gen. Tech. Rep. RMRS-GTR-282. 2012 51

Groundwater

Fens, wet meadows, and some salt flats are groundwater-dependent wetlands, with 

plants deriving most of their water from a shallow water table. Understanding the 

sources, flow paths, seasonal dynamics, and interactions with the soil surface is critical 

for managing the hydrologic driver of these ecosystems. Groundwater can flow from 

bedrock or from unconsolidated aquifers, or it can be recharged by surface waters such 

as streams and lakes. A single wetland may have more than one groundwater source. 

For example, different parts of a single wetland complex may be supported by a bedrock 

aquifer and groundwater associated with a glacial moraine, each source having distinct 

chemical composition and seasonality.

As previously mentioned, two primary types of instruments are used to measure 

groundwater in wetlands: water table monitoring wells and piezometers. Water table 

monitoring wells are used to measure the water table, which is unconstrained by 

confining sediment layers (e.g., open to the atmosphere) and is in equilibrium with 

atmospheric pressure. A piezometer is used to measure the pressure head in a soil or 

bedrock layer or at a particular depth below the water table. Other techniques for measuring groundwater are available (e.g., ground penetrating radar) but are more costly 

and require expensive equipment (McClymont and others 2011).

Installation of instruments

A water table monitoring well can be installed using a hand auger, a handheld or vehicle mounted machine auger, or a backhoe (Figure 4-5). In many 

wetland settings, especially in peatlands and wetlands with sand/silt substrates, an option for installing water table wells or piezometers is to drive them. 

Figure 4-5. Hand augers can be used to bore holes for 

installing a groundwater monitoring well. Mounted power 

augers may be used in cobble or hardpan substrate.
52 USDA Forest Service Gen. Tech. Rep. RMRS-GTR-282. 2012

Driven wells have the advantage of not requiring augering. Driven wells can, 

however, be problematic in areas with substantial clay content in the substrate 

or a hardpan. The hole or pit must not penetrate any confining layers and should 

be deep enough that the water table can be measured in any season and in any year. 

A hand-augered well could consist of a 2.5 to 10 cm (1 to 4 inches) diameter bore 

hole, and the layers of material that are bored through should be logged. A hand 

driven well casing can have its slots or holes filled with clay or other particles and 

the well rendered inoperable. The water table should be encountered when augering 

this hole, although in very fine grained sediments with very low porosity, the water 

table may not be apparent. Iron and manganese mottles or streaks (orange or black 

spots that can range from a few millimeters to a centimeter in width) may occur 

near the top of the seasonal water table.

Wells should be installed during the dry season, if possible, when the seasonal water 

table is deepest. It also can be difficult to remove sediment from a hand-augered bore 

hole when augering below the water table because the saturated sediment is likely to 

flow from the auger head. The well should extend below the water table allowing its 

measurement in the driest season and in a dry year.

A section of PVC pipe should be placed in the bore hole. The pipe should have 

machine slots or hand installed slots sawn into the pipe using a hacksaw, or it 

should have holes created with a drill. The slots should extend from the bottom of 

the casing to just below the ground surface. The holes and saw cuts should be as 

thin as possible so that sediment from the bore hole will not enter and fill the well 

casing. A filter fabric may be wrapped around the PVC to exclude sediment, but 

often is not needed. The bore hole around the casing can be filled to near the ground 

surface with clean sand or gravel of slightly larger diameter than the slots or holes. 

In many instances, the hole can be simply backfilled with native soils. The bore hole 

should be bailed using a commercial well bailer until fresh, clean groundwater fills the 

hole. This is especially needed when the water is muddy or contains shreds of partly 

decomposed peat. A bottom cap should be installed prior to placement and have a hole 

drilled through it to allow water to freely drain from the PVC if the water table drops 

below the bottom of the slots. A top cap is needed to keep rain and debris from the well 

casing. A monitoring well can also be used as a staff gauge to measure surface water 

height. In the case where the well would be used both as a groundwater and surface water 

monitoring device, slots or holes could be placed above the ground surface. However, 

in some cases, it is informative not to slot monitoring wells above the ground surface 

and to place clay, such as bentonite, or concrete in the top several inches of the bore 

hole so that surface water does not enter the sand or gravel pack around the well casing.

A piezometer is a solid section of small-diameter PVC pipe that is open only on the 

ends. In relatively soft soil such as peat or in moist to wet, fine-grained sediment, the 

PVC can be pushed to the correct depth. The bottom depth of the piezometer should 

be determined from the logged borings of the monitoring well. A piezometer can be 

installed into any soil layer for which information on pressure head is desired. A simple 

piezometer can be made from a section of small-diameter (e.g., 1.3 cm inside diameter) 

PVC pipe that is long enough to reach the depth to be measured, plus a suitable height of 

pipe to extend above the ground surface, typically at least 20 cm (Figure 4-6). A section 

of solid steel or aluminum rod (an electrical grounding rod that is copper coated steel 

can also be used and can be easily purchased in large hardware stores) longer than the 

PVC should be inserted into the PVC so that the bottom end sticks out 1 to 3 cm. The 

rod is held in place by locking pliers where the PVC pipe contacts the rod. The rod is 

held vertically with the locking pliers near the top, and the PVC assembly can be pushed 

to the desired soil depth.
USDA Forest Service Gen. Tech. Rep. RMRS-GTR-282. 2012 53

The pliers are used to pull the rod out of the PVC once it is inserted to the desired 

depth. Piezometers of this design are typically placed at several depths relative to the 

monitoring well to create a piezometer “nest” (Figure 4-7). Care should be taken not 

to auger or drive through confining sediment layers that separate aquifers. Connecting 

otherwise isolated aquifers may lead to the collection of data that is erroneous or difficult to interpret.

In harder material, piezometers can be constructed using augered holes. The hole 

should terminate at the depth the piezometer end will be placed. The PVC pipe can be 

slotted through the bottom 10 to 20 cm of pipe and a solid end cap should be installed. 

The slotting should match the soil layers that you wish to monitor. The PVC should be 

placed into the hole, and coarse sand should be used to fill the bore hole to the top of 

the slotted PVC. A layer of bentonite 20 cm or more thick should then be put over the 

sand, tamped in place, and wetted to encourage the clay to swell and seal the bore hole. 

Figure 4-6. (Top) Small-diameter PVC pipe 

with solid metal rod inserted through the 

pipe and a pair of pliers holding the rod in 

place. (Bottom left) Metal rod held by pliers 

is inserted into PVC and pushed into soil. 

(Bottom center) Metal rod is being removed. 

(Bottom right) Completed piezometer.
54 USDA Forest Service Gen. Tech. Rep. RMRS-GTR-282. 2012

The remaining hole can be filled with sediment removed during the boring, coarse sand, 

or other material. The upper part of the bore hole fill may be capped with bentonite or 

cement, as previously discussed.

Where soil material is too coarse or dry to auger through cobble, a drive point well 

may be installed (Figure 4-8A and B). Each has a cast iron drive point (red tip in Figure 4-8A) and a stainless steel slotted section (silver) with a threaded end. Threaded 

couplers are used to connect sections of unslotted steel pipe. A threaded drive cap is 

installed onto the steel pipe, and a fence post pounder is used to install the well to the 

desired depth (Figure 4-8B). Care must be taken to lubricate the coupler, and, using 

pipe wrenches, thread the coupler tightly onto the drive point and the steel pipes. If the 

coupler is not completely threaded on, the pounding will strip the threads. It is even 

more critical to get the drive cap lubricated and threaded completely onto the threaded 

end of the steel pipe. This facilitates driving and removing the drive cap to install an 

additional coupler and section of steel pipe.

Figure 4-7. A well nest consisting of one water table well (right) and two piezometers. 

Figure 4-8. Steel drive points 

can be pounded into the ground 

to create water table monitoring 

wells or piezometers. 

A B
USDA Forest Service Gen. Tech. Rep. RMRS-GTR-282. 2012 55

Measurement

Staff gauges can be read directly from the numbers on the staff face or as distance 

from the top of the staff gauge to the water surface measured with a ruler. Monitoring 

wells can be measured with any commercial measuring tape (Figure 4-9). Weighted chalk 

lines and stereo wire connected to a weight and an ohm meter may also be used. The 

tape should be used to measure the distance from the top of the well casing to the water 

surface. This measurement must be 

corrected for the well casing height 

above the ground, which is called 

the “stick up” height of the pipe. The 

stick up height should be subtracted 

from the total depth to water table 

from the casing top to determine the 

depth to the water surface below the 

ground surface. Piezometers should 

be similarly measured. It is critical 

to get accurate stick up heights for 

all water table wells and piezometers.

Groundwater chemistry can be 

useful for diagnosing one or more 

sources of waters. Water within 

monitoring wells can be measured 

directly after first bailing the well casings out at least twice to allow fresh 

groundwater to enter the pipe. Water 

in streams, ponds, or monitoring 

wells can be directly measured using 

an electrical conductance meter, or 

water can be collected for analysis of 

cations, anions, or nutrients.

Redox potential

Water is denser than air, and when soils flood or a water table rises to saturate soils, 

water forces air out of the soil interstices. If the soils are warm enough for biological 

activity, then bacteria and plant roots can remove the remaining dissolved or trapped 

oxygen (O2) in the soil. At this point, the soil is anaerobic or anoxic, meaning that it lacks 

free O2. Plants that must obtain O2 for root metabolism directly from the soil they are 

rooted in will drown if the soils remain anoxic for more than a couple of weeks during the 

growing season. Once free O2 in the soil is depleted, bacteria that can use molecules other 

than oxygen as their terminal electron receptor for respiration processes become active. 

Since electrons have a negative charge, when an electron is added to a molecule such as 

ferric iron (Fe3+) or manganic manganese (Mn4+), it reduces (makes more negative) the 

molecule’s electrical charge, producing ferrous iron (Fe2+) or manganous manganese 

(Mn2+). This process is called reduction and such soils are considered to be “reducing”. 

A series of biogeochemical changes occur in soils as they become increasingly reduced, 

with oxidized forms of nitrate (NO3

-

), Mn4+, Fe3+, sulfate (SO4

-

), carbon dioxide (CO2), 

and hydrogen (H) being reduced. Reduced forms of Mn and Fe are soluble in water, and 

plants that uptake them can suffer heavy metal poisoning. Nitrogen reduction removes 

NO3 from the soils by producing gaseous N. Hydrogen sulfide (H2S), formed by the 

reduction of SO4, is toxic to plant roots. Carbon dioxide reduction forms the important 

greenhouse gas methane (CH4).

Figure 4-9. Manual measure of water table depth in 

monitoring well using a tape measure.
56 USDA Forest Service Gen. Tech. Rep. RMRS-GTR-282. 2012

Redox potential is a measure of the oxidation state of various reduction couples in 

soils. The soil oxidation-reduction potential can be measured with a millivolt meter 

using a pure platinum tipped electrode coupled with a reference electrode to complete 

the redox circuit. The platinum must be pure (>99 percent platinum) wire and thick 

enough that it can be inserted into the soil, such as 18-gauge wire. An approximately 

1 cm long piece of platinum must be fused to copper or brass wire or rod without the 

introduction of an additional metal such as solder. If copper is used, it should be pure. 

The copper or brass is heated with a torch until it just melts. While heating the copper, 

the 1 cm long piece of platinum wire is held with a pair of needle nose pliers. When 

the copper melts, the heat is removed and the platinum wire is touched to the copper 

simultaneously, allowing the metals to fuse. The copper and fused junction must then be 

sealed using waterproof heat shrink tubing or another substance. The junction between 

the platinum and copper must be completely sealed because any copper exposed to the 

soil environment will foul the circuit. Detailed instructions for making platinum tipped 

electrodes are presented in Wafer and others (2004) and in Mitch and Gosselink (2000).

The platinum electrode is inserted into the soil to the depth desired for measurement. 

A calomel (Ag/Cl) reference electrode is also inserted into the soil, and both electrodes 

are attached to a millivolt (Mv) meter, which measures the electron flow in Mv. Most 

high-quality pH meters have a Mv mode. The reference electrode is attached to the reference jack, and the platinum electrode must be fitted with a Bayonet Neill-Concilman 

(BNC) end to attach to the pH electrode jack. The Mv readings must be corrected for 

the reference electrode by adding +244 Mv to the reading. In addition, pH can influence redox readings, and the raw data must be corrected by -60 Mv per pH unit greater 

than or less than 7.0.

It is most reasonable to use redox potential to provide an indication of the general 

oxidizing or reducing condition of the soil. Broad distinctions such as oxic (free O2 is 

present in the soil, and redox potential >+400 Mv), moderately reducing (+100 to +400 

Mv), reduced (+100 to -100 Mv), and highly reduced (-100 to -300 Mv) are suggested 

(Bohn 1971).

Soil redox potential can be highly variable depending upon the microhabitat that 

the platinum electrode contacts in the soil. Therefore, it is suggested that at least three 

electrodes be installed at each soil depth of interest. In practice, it’s best to install the 

electrodes and leave them in place for the entire study period to disturb the soil as little 

as possible. Redox potential measures are most reliable in saturated and reduced soils. 

Measures should be performed often enough to allow the seasonal patterns of redox 

potential to be revealed. The measures are most useful if coupled with a groundwater 

monitoring well that is equipped with a pressure transducer in order to record daily 

water levels at the study site. This is particularly important in sites with highly variable 

hydrologic regimes. For example, a researcher may visit a field site that has saturated 

soils on the day of the visit but he/she may measure oxic soils. This would make sense 

if the site had recently become saturated and had insufficient time for reducing conditions to develop. However, the opposite could also happen. A site could appear dry at 

the surface but because of previous hydrologic conditions, it could have been saturated 

for many weeks and the soils could be reducing as it may take days to weeks for air to 

reach the soil depths being measured (particularly in fine-textured soils). Thus, data on 

recent hydrologic patterns and processes are critical for interpreting soil redox potential 

measurements.

Soil redox potential is as important to plant species distribution as is water table 

depth or its duration. This is because highly reducing conditions produce inhospitable 

environments that relatively few species can survive.
USDA Forest Service Gen. Tech. Rep. RMRS-GTR-282. 2012 57

Data presentation

Water table wells and piezometers

Depth to water for monitoring wells can be illustrated as simple line graphs showing 

the trends in one or more wells relative to the ground surface (Figure 4-10A) or true 

elevation of the water level (Figure 4-10B). This allows a direct comparison of water 

levels among wells. In Figure 4-10A, water levels for 15 wells are compared for two 

summers for Cottongrass Fen in Colorado’s San Juan Mountains. The year 2003 was 

dry and water levels in many wells dropped well below the ground surface, while 2004 

was a near average snow year and water levels for most wells remained near the soil 

surface (other than well CW11). Figure 4-10B compares a staff gauge in the Merced 

River (X16) and 10 monitoring wells (33-77) on the Yosemite Valley floor in Yosemite 

National Park, California, using true elevation of the groundwater and surface water.

Water levels in piezometers should be compared to each other and to the adjacent 

monitoring well (Figure 4-11). A piezometer with head higher than the water table 

indicates an upward hydrologic gradient in the sediment layer being monitored by the 

piezometer. A piezometer with head lower than groundwater in the well indicates a 

downward gradient, while a similar head (relative height of water surface) and water 

table indicate minimal vertical flow and suggest that groundwater flow is roughly horizontal. In Figure 4-11, SpW1 has downward flow in the piezometer with a terminus at 

147 cm below the soil surface, while the other piezometers have heads above the water 

table. All piezometers at site SpW2 have upward flow in all three years, while at StW2 

flow is primarily horizontal.

Cross sections and profiles

Cross sections and longitudinal profiles that illustrate both the land surface and the 

water table and/or piezometric head are important tools for showing the relationship of 

the water table to the land surface over large areas, and they can be used to infer flow 

direction.

Figure 4-10. (A) Water table presented as depth below ground surface and (B) as elevation for multiple wells. 

A B
58 USDA Forest Service Gen. Tech. Rep. RMRS-GTR-282. 2012

Figure 4-11. Nests of one water table monitoring wells (W) and three 

piezometers (P) located adjacent to each well. SpW1 is Spruce fen 

Well 1, SpW2 is Spruce fen Well 2, and StW2 is String fen Well 2 in the 

Prospect Basin area of the San Juan Mountains near Telluride, Colorado. The green lines are the water table depth below the soil surface 

(0), and the three piezometers are used to measure the head at three 

depths in each location. The completion depth, in centimeters, is listed 

for piezometers.
USDA Forest Service Gen. Tech. Rep. RMRS-GTR-282. 2012 59

Figure 4-12. A 1200 m long transect 

across the western side of Tuolumne 

Meadows in Yosemite National Park, 

California. Water levels recorded in 15

monitoring wells (numbered) and 1 staff 

gauge (SG) are shown for four dates 

during 2006. The Tuolumne River is 

at right, and a hillslope bordering the 

meadow is at left. The Tioga Pass highway 

is shown at ROAD. 

Figure 4-12 is a 1200-m longitudinal profile across the western portion of Tuolumne 

Meadows in Yosemite National Park, California, that shows the ground surface elevation 

and groundwater levels for four dates during 2006. The wells near the road are in upland 

conifer forests (wells 62, 56, 55), while the other wells are in wet meadows. Groundwater flows from the uplands on the left toward the Tuolumne River on the right. Wells 

10, 11, and 71 appear to have water levels that closely follow the river stage, indicating 

that these are riparian sites, while the remainder of the meadow along this transect is a 

groundwater-fed wet meadow.

Many mountain streamside wetlands are groundwater-fed and supply streams with 

water, as can be seen for Snow Spur Creek on Lizard Head Pass at the headwaters of the 

Dolores River in Colorado (Figure 4-13A and B; cover photo). In this area, Snow Spur 

Creek is a gaining stream. The San Miguel River, near Uravan, Colorado, is a losing 

reach, with a higher stream stage than the adjacent floodplain groundwater elevation.

Water table maps

Water table elevations for wells that are organized in a spatial grid can be used to 

make a two-dimensional water table map that illustrates the overall water table elevation 

as well as the direction and gradient of groundwater flow. The map in Figure 4-14 for 

Tuolumne Meadows shows groundwater flow from the south side of the valley toward 

the channel (gaining reach) and flow that is parallel with the Tuolumne River in the 

right side of the diagram. Flow is from right to left.

A water table map can also be used to show water table contours near a stream, such 

as for the Snake River in northwest Wyoming (Figure 4-15). This figure shows groundwater flow within a floodplain, with water having been lost from the river upstream 

near letter A and flowing back to the river downstream near B.

The water table elevation can also be portrayed as a color contour map, shown for 

Yosemite Valley on 17 May 2006 (Figure 4-16). This figure shows groundwater flow 

from north to south from Ahwahnee Meadow and from south to north from Stoneman 

Meadow. Both groundwater flow systems feed the Merced River, which is flowing 

from right to left.
60 USDA Forest Service Gen. Tech. Rep. RMRS-GTR-282. 2012

Figure 4-13. Ground surface and surface and groundwater elevations on two profiles. 

Snow Spur Creek (top) and San Miguel River (bottom).

Figure 4-14. Water table contour map of Tuolumne Meadows, Yosemite National Park, California, for 18 September 2006. From Cooper and others (2007).
USDA Forest Service Gen. Tech. Rep. RMRS-GTR-282. 2012 61

Figure 4-15. Water table contour map for the Snake River floodplain at Flagg Ranch, Wyoming, with arrows 

indicating the direction of flow. From Cooper and Patterson (2007).

Figure 4-16. Water table contour colored map of Yosemite Valley. From Cooper and Wolf 

(2006).
62 USDA Forest Service Gen. Tech. Rep. RMRS-GTR-282. 2012

Depth to water table map

The water table depth below the ground surface may also be presented in twodimensional map form. This type of figure (Figure 4-17) should be presented for different seasons (for example, early summer and late summer) or for a wet versus a dry 

period. It can be used to highlight areas affected by ditches and the effect of restoration 

on the water table depth; for example, the restoration of Big Meadows fen in Rocky 

Mountain National Park, Colorado (Figure 4-17; top panel is before ditch restoration, 

bottom panel is after restoration).

Data management

The management of data is essential to storing and using data for short-term and 

long-term analyses. Raw and post-processed data can be stored using any spreadsheet 

program or database. An example of the data that should be collected in the field and 

used to produce a high-quality data set is shown below (Table 4-1). For each water 

table well or piezometer, the well number, total length of the PVC pipe, length of pipe 

below the ground surface, and length of pipe above the ground surface (stick up) must 

be accurately recorded. The elevation of the casing top should be accurately determined. 

Figure 4-17. Depth to water table map for Big Meadows, Rocky Mountain National Park, Colorado. From Cooper and others (1998). 
USDA Forest Service Gen. Tech. Rep. RMRS-GTR-282. 2012 63

Table 4-1. Well number, total length of PVC pipe used to create the well, length of PVC belowground, length of pipe aboveground 

(“Stick up”), elevation of the casing top (“Case elevation”), depth to the water table from the top of casing (“07-Jul-08”), 

depth to the water table below ground surface (“WT depth”), and the elevation of the water table (“WT elev.”). All units 

are meters.

Well # Total length Belowground Stick up Case elevation 7-Jul-08 WT depth WT elev.

1 3.12 2.91 0.21 3221.65 1.58 1.37 3220.07

2 2.75 2.55 0.20 3222.05 2.20 2.00 3219.85

3 1.68 1.45 0.23 3221.90 1.55 1.32 3220.35

4 3.85 3.60 0.25 3223.20 3.22 2.97 3219.98

5 2.99 2.71 0.28 3223.20 2.26 1.98 3220.94

Raw measures of water table depth should be entered completely, under a column for the 

date on which the measures were made. The raw measure from the casing top includes 

the stick up length, which should be subtracted from the raw measure to calculate water table depth below the ground surface. The raw measure should be subtracted from 

casing elevation to determine elevation of the water table. Water table depth is used to 

create hydrographs and maps of water table depth, while water table elevation is used to 

create profiles and cross sections, and water table elevation maps. Each period of data 

collection could be entered into this spreadsheet in a column to the right of the 7 July 

2008 data. The water table depth and water table elevation calculations could occur on 

a linked worksheet.

Topographic surveying

Accurate topographic data on 

the true or relative elevation of the 

ground surface and on the location and elevation of measuring 

instruments is essential for almost 

all hydrologic investigations. If a 

single monitoring well is being 

analyzed and depth to the water 

table is the only measurement 

needed, then accurate topographic 

information may not be necessary. 

However, to understand the 

relationship between two wells 

or sets of instruments of any 

kind, topographic information 

is needed. Topographic surveys 

can be conducted with a variety 

of instruments, including laser 

total stations (Figure 4-18) and 

GPS based surveying equipment, or a more traditional 

survey can be conducted that

utilizes level or theodolite to 

measure distances and angles 

Figure 4-18. Topographic surveying with full station in 

Death Valley National Park, California.
64 USDA Forest Service Gen. Tech. Rep. RMRS-GTR-282. 2012

between points. A topographic map can help a researcher decide where to install instruments and is critical for making water table maps. Cross sections and profiles can be 

generated if the distance between wells is calculated using a tape measure and if the 

relative height of each well is measured using a rod and level. Detailed descriptions of 

surveying are presented in Harrelson and others (1994), which is available at: http://

www.stream.fs.fed.us/publications/PDFs/RM245E.PDF. Guidelines for surveying cross 

sections, measuring flow velocity, and calculating stream discharge are provided in 

Buchanan and Somers (1976), which is available at: http://pubs.usgs.gov/twri/twri3a8/

html/pdf.html.

Hydrologic study design

The spatial distribution of instruments and the types of instruments used depend 

upon the landscape being analyzed, the questions being addressed, and the skills of 

the researcher. Measuring devices (instruments) may be aligned along transects where 

known gradients exist; for example, traversing an upland-wetland gradient or a stream 

channel-floodplain gradient (Figure 4-19). A grid is suitable where unknown hydrologic 

patterns and processes are being investigated and where the construction of a water table 

map is desirable. Hydrologic investigations may also focus on the known or observed 

distribution pattern of plant communities or on other ecological or hydrologic processes. 

Figure 4-19. Distribution of monitoring wells (red numbers) in Yosemite Valley, California. These wells are set as 

a series of transects that investigate the relationships of upland to lowland, river to floodplain. The transects are 

oriented parallel to and perpendicular to each other, which facilitated construction of water table maps. From Cooper 

and Wolf (2006).
USDA Forest Service Gen. Tech. Rep. RMRS-GTR-282. 2012 65

This allows for the collection of data on resources of interest and for the comparison of 

water levels among plant community types.

Groundwater-surface water interactions

The interactions of surface water and groundwater support many key functions of 

streams and link ecosystems through water and nutrient exchanges. Several patterns 

provide strong evidence for the linkage between surface and groundwater. If stream 

stage is nearly identical to the pattern and rate of change of groundwater, they are most 

likely connected, rising and falling in tandem (Figure 4-20). This can also be shown in 

a profile oriented at 90 degrees to the flow direction of the river (Figure 4-21). In this 

example, stream stage is higher in elevation than groundwater in any monitoring well 

for the four measurement dates, suggesting flow from the river into the floodplain soils.

Figure 4-20. Stream stage is completely correlated with groundwater levels in five 

monitoring wells on the floodplain of the San Miguel River in southwestern Colorado. 

This suggests that stream water supplies and controls the elevation of groundwater 

in this location. From Cooper and Arp (1999).

Figure 4-21. Measures of relative stream stage and groundwater levels along 

the San Miguel River in Colorado. Each symbol is a staff (river) or well, and their 

distance from the river staff is measured in meters. From Cooper and Arp (1999).
66 USDA Forest Service Gen. Tech. Rep. RMRS-GTR-282. 2012

Surface water and groundwater interactions can also be shown with water table maps. 

This requires both staff gauges in the stream and a network of monitoring wells. All wells 

and staff gauges must be topographically surveyed for position and elevation. Where 

the flow net (water surface and water table elevations) indicates movement of water 

from the river to floodplain, it strongly suggests groundwater recharge by the stream 

(Figure 4-22). Surface water and groundwater interactions can also be investigated using geochemical comparisons of surface water and groundwater by adding tracers to 

surface water and other techniques.

Figure 4-22. Water table map for the San Miguel River, near the Uruvan 

gauge, showing 0.5-m contour lines. Monitoring well and staff locations are 

identified. The flow net indicates strong flow from the river into the floodplain 

in certain areas, such as the bottom of the figure, and on river right from 

150 to 300 m along the y axis. In other areas, groundwater flow parallel with 

the river is indicated by flow lines perpendicular to the river. From Cooper 

and Arp (1999).
USDA Forest Service Gen. Tech. Rep. RMRS-GTR-282. 2012 67

Hydrologic impact analysis: Groundwater pumping

Groundwater is pumped for human use in many areas of the world. Water pumped 

from shallow depths may influence the local or regional water table elevation. A groundwater pumping well occurs in Crane Flat meadow in Yosemite National Park and its 

effects have been analyzed (Figure 4-23A; blue dot within the black rectangle). A grid 

of nested water table wells and piezometers was established across Crane Flat (Figure 

4-23B). Three well/piezometer nests—A-1, A-2, and A-3—are illustrated here (Figures 

4-23C and D). Figure 4-23C illustrates three water table well and piezometer nests (A1, A-2, and A-3); the water table is indicated by the white bar with cross hatching and 

piezometers are indicated by the solid bars. The ground surface (top of gray shading) 

and the soil zones that are saturated (blue) and unsaturated gray. Figure 4-23C shows 

a period in early summer prior to the initiation of pumping, while Figure 4-23D shows 

the same site during the mid-summer pumping period. The decline of the water table 

(shown as the top of the blue shaded area) is apparent, as are the heads in the piezometers 

(shown as red triangles across each piezometer). A continuous logger in well 49 (Figure 

4-23E) illustrates the rapid drawdown during July and August, with diurnal fluctuations 

created by pumping for approximately 12 hours per day and a rain in October that led 

to water table recovery.

Figure 4-23. Location of monitoring wells (A), detailed view of well networks, 

including nests of wells and piezometers (B, C, and D) and patterns of hourly 

water levels as influenced by pumping. Pumping ceased in late October. 

Light blue area in (C) and (D) indicates groundwater level in early July (C) 

versus mid-September (D). From Cooper and Wolf (2007).

A
68 USDA Forest Service Gen. Tech. Rep. RMRS-GTR-282. 2012

Figure 4-23. (Continued)

C
USDA Forest Service Gen. Tech. Rep. RMRS-GTR-282. 2012 69

Figure 4-23. (Continued)

D

E
70 USDA Forest Service Gen. Tech. Rep. RMRS-GTR-282. 2012

Hydrologic impact analysis: Changes in stream flow

Stream flows have been altered by human constructed dams, water diversions, and 

other structures. Climate change during the past 100 years has also been shown to have 

changed the flow of many streams (Karla and others 2008). Two methods for showing 

changes in stream discharge are plotting mean daily flows and annual instantaneous 

peak flows. Figure 4-24 plots the mean daily flow for the Green River at the Greendale in Wyoming, located just below Flaming Gorge Dam. The dam was completed 

in 1962 and altered stream flows starting in spring 1963. Flows below the dam were 

nearly curtailed during 1963 and 1964, and post-dam peak flows were reduced in most 

years compared with pre-dam years. Base flows have been increased, thereby reducing 

annual flow and stage variance. Through the early 1990s, a single seasonal snowmeltdriven period of high flow did not occur, and high and low flows occurred throughout 

the year due to dam operations. Five high flows occurred in the 1980s and 1990s when 

the reservoir pool filled following winters with very large snowpack in the headwaters. 

Flow management produced a seasonal single peak beginning in the 1990s to meet the 

needs of federally listed endangered native fishes. Figure 4-25 illustrates instantaneous 

annual peak flows and the striking difference between pre-and post-dam years. Most 

post-dam years have nearly identical peak flows due to the capacity of the electricity 

generating turbines to pass water at a rate of 130 m3/s (4600 ft3/s).

Commercial software is available for characterizing streamflow regimes and for 

analyzing hydrologic impacts to streams. Indicators of Hydrologic Alteration (IHA) is 

software that calculates 64 statistics summarizing daily average flow data either beforeand-after date of impact or over time (range of variability analysis). IHA software and 

instructions for its use are available from: http://conserveonline.org/workspaces/iha/

documents/download/view.html. Olden and Poff (2003) reviewed metrics for characterizing streamflow and linking them to biological patterns, including many of the metrics 

generated in IHA.

Figure 4-24. Mean daily discharge of the Green River at the Greendale (USGS gauge number 09234500) and Linwood (USGS gauge number 09225500) gauges in Utah. No data were 

collected prior to 1912 and between 1915 and 1929. 
USDA Forest Service Gen. Tech. Rep. RMRS-GTR-282. 2012 71

Figure 4-25. Instantaneous peak discharge of the Green River at the Greenwood and Lindale gauges, Utah. 
72 USDA Forest Service Gen. Tech. Rep. RMRS-GTR-282. 2012
USDA Forest Service Gen. Tech. Rep. RMRS-GTR-282. 2012 73

Chapter 5: Linking Riparian and Wetland 

Vegetation to Hydrologic Factors

As discussed in Chapter 3, water is a principal limiting resource for plants, and a 

number of vegetation attributes are supported by and respond directly to water availability. In addition to direct measurements of plant characteristics at the level of the 

individual (such as water status, transpiration, water source, and incremental growth), 

attributes of vegetation may be measured at the population and community levels. Plant 

fitness, vulnerability to pathogens and herbivores, fecundity, competitive ability and 

productivity, population structure, and community composition and richness are influenced by water availability in space and time. Each vegetation attribute that could be 

measured at each of these levels varies in what it reveals about the characteristics of the 

vegetation. Each attribute also varies in its sensitivity to altered water availability and 

its interrelationship with other environmental and biological factors not associated with 

flow regime (Table 5-1). Most plants have optimum soil water conditions for growth 

that lie somewhere between saturated (and anoxic) and dry. This may change over the 

life span of the species (different for seedlings compared to adults) and over the season 

(e.g., higher during the height of the growing season compared to when plants are dormant). In this section, we discuss how to link the measurable characteristics of plants 

and vegetation (Chapter 3) to surface water, soil water, and groundwater measurements 

(Chapter 4). These tools are useful in modeling the distribution and fitness of plants 

and characteristics of vegetation along moisture gradients; making educated predictions 

of likely changes in response to altered hydrologic regimes; and informing decisions 

on proposed water extraction, groundwater pumping, and prescriptive and managed 

hydrologic regimes along rivers, streams, marshes and lakes.

Table 5-1. Metrics of riparian vegetation and sensitivity to hydrologic alteration and ability to reflect responses to 

chronic changes in flow regime. Number of asterisks indicates the authors’ conceptions of relative strength. 

From Merritt and others (2010a).

Acute sensitivity to Reflective of chronic

Organizational level Metrics hydrologic alteration hydrologic alteration

Individual xylem water potential **** ***

 transpiration **** *

 photosynthesis **** *

 CO2 flux **** *

canopy volume **** *

shoot/root growth *** *

incremental growth **  

leaf size **  **

leaf thickness ** **

Population age/stage/size class distribution * ****

population growth rate * ****

 variability * ****

Community richness * **** (varies)

diversity * **** (varies)

 composition **  

 cover ** * ****

Stand Structure/ biomass ***  

Productivity vegetation volume **  ****

vertical structure ** ****
74 USDA Forest Service Gen. Tech. Rep. RMRS-GTR-282. 2012

Vegetation response to changing hydrologic regimes may be directional such as the 

decline and collapse of existing plant populations, the establishment of new populations, 

or shifts in the zonation of vegetation. Response may also involve more complex and 

less directional shifts or abrupt changes in individual fitness, population structure, or 

species composition. A number of plant responses to altered water availability occur 

over different time scales ranging from hours to decades, and there may be lag times 

between hydrologic alteration and plant responses. Furthermore, different life stages 

of the same species may respond in different ways to the same hydrologic alteration.

In general, measures of the physiological characteristics of individual plants may 

be the most sensitive indicators of short-term changes in hydrologic regime, but may 

reveal little about the long-term ecological consequences of changes in water availability. 

Measures of the attributes of a population of a particular species or multiple species at 

the reach scale may better reveal changes in flow regime over longer periods of time, but 

may be less sensitive to subtle changes. In turn, attributes measured at the scale of the 

plant community may more reliably reveal long-term patterns of hydrologic regime. The 

choice of measurement at the scale of the individual, population, community, or some 

combination largely depends upon the vegetation attributes that are deemed important 

along with established goals for maintenance and restoration of wetland and riparian 

vegetation. Measures of plant attributes at each of these levels of organization as well 

as methods for understanding linkages between hydrology and individual, population, 

community, and functional attributes of vegetation are presented in the following sections.

Individual plants

Individual plants must germinate/sprout, grow, mature, reproduce, and die to contribute 

to a population (Figure 5-1). The likelihood of transitioning from one stage to the next 

in this cycle depends on the environment and the individual’s traits for dealing with the 

environment. The same environmental factor may pose a different risk to individuals at 

each stage in development, influencing the rates of birth, growth, maturation, fertility, 

Figure 5-1. Life cycle of plants. In order to sustain a population, individual plants must successfully transition from 

one stage to the next over some time interval that is less 

than the maximum life expectancy of the plant.
USDA Forest Service Gen. Tech. Rep. RMRS-GTR-282. 2012 75

and mortality. Knowledge of the individual life history (requirements and tolerances at 

different life stages) of a species relative to the physical environment is necessary for 

developing cause-and-effect relationships between attributes of hydrology and life stages 

of that species (Figure 5-2). Such information can be gleaned from peer-reviewed literature, textbooks, online databases, and/or personal experience and field measurements.

Any of the fitness variables measured on individual plants may be linked to hydrologic characteristics using standard statistical techniques. For example, xylem water 

potential or photosynthesis may be related to depth to water or streamflow volume using 

regression. Measurements of water stress of an individual (or several individuals) may 

be taken while water availability is changing (e.g., groundwater pumping causing depth 

to groundwater to change). For example, Cooper and others (2003b) measured xylem 

water potential of several cottonwood trees while groundwater pumping was causing 

lowering of water tables (Figures 5-3 and 5-4). Regression revealed relations that could 

then be used to provide guidance on how deep the groundwater could be pumped before 

dangerous or mortal stress levels were reached.

Figure 5-2. Linking each stage in the life cycle provides tools for managing water availability 

to provide for survival at each of the life stages and to accommodate transition from one 

stage to the next.

Figure 5-3. Linear regression of predawn xylem pressure potential along the 

maximum water table drawdown gradient 

for unwatered plots. Watered plot means 

are also shown. Error bars are ±1 SE. From 

Cooper and others (2003b).
76 USDA Forest Service Gen. Tech. Rep. RMRS-GTR-282. 2012

Figure 5-4. Polynomial regression of 

percent leaf loss along the maximum water 

table drawdown gradient for unwatered 

plots. Watered plot means are also shown. 

Error bars are ±1 SE. From Cooper and 

others (2003b).

Scott and others (1999) investigated the relations between tree survivorship, tree crown 

volume (measured as a percent change over time), incremental stem growth, and branch 

growth and depth to water table (Figure 5-5). They found that crown volume is tightly 

linked to depth to groundwater and that tree mortality is a function of the previous year’s 

crown volume. They used logistic regression to model the probability of tree survival 

as a function of previous year’s crown volume and found that trees with no change in 

crown volume had a 97 percent chance of survival, whereas those that experienced 30 

percent or more loss in crown volume had less than a 50 percent chance of survival.

Figure 5-5. Measured attributes of cottonwood as a function of change in water availability (change 

in groundwater elevation) during groundwater pumping associated with mining. From Scott and 

others (1999).
USDA Forest Service Gen. Tech. Rep. RMRS-GTR-282. 2012 77

Linear regression can be performed in any standard statistical software, many plotting 

software packages, and spreadsheet programs such as Microsoft Excel. Logistic regression models binary (e.g., presence-absence or survival-mortality) data measured along a 

gradient. Generalized linear models (GLM) (e.g., logistic regression for presence-absence 

data and Poisson regression for count data) can be fitted in standard statistical software 

programs. Add-ons to Microsoft Excel may also be used to conduct generalized linear 

modeling (e.g., http://sunsite.univie.ac.at/Spreadsite/poptools/index.htm or http://www.

statisticalengineering.com/glm.htm).

In addition to modeling plant attributes as a function of hydrologic variables, comparisons between control and treated areas may also be conducted. One such comparison 

could be upstream to downstream from a diversion or in an area of interest (treatment) 

versus an area used for comparison (control). In a study of a diverted creek in Arizona, 

xylem pressure was found to be lower (more water stress) in native trees along a reach 

that had been dewatered as compared to a free-flowing reach upstream from the water 

diversion (Figure 5-6).

If relationships between attributes and water availability are strong (e.g., high 

r-square and low p-value), they may be used to predict plant conditions under a variety 

of water availability scenarios. If the relationships are weak, it probably means that 

other factors (hydrologic and otherwise) are more important than the one measured. If 

multiple hydrologic factors are thought to be influencing plant characteristics, multiple 

regression analysis may be used to model conditions as a function of multiple variables.

Figure 5-6. Box plots of pre-dawn and midday xylem water potential for three native tree species (Platanus

arizonica, Populus deltoids, and Salix gooddingii) and a non-native (Tamarix spp.). T-tests comparing 

the mean midday water potential upstream and downstream from a diversion indicated that the native 

species all experienced low water potentials downstream from the diversion, but the non-native species 

exhibited drought tolerance.
78 USDA Forest Service Gen. Tech. Rep. RMRS-GTR-282. 2012

Plant recruitment and establishment

Recruitment into a population first requires that seeds or vegetative propagules reach 

suitable sites, germinate, and survive. In many wetlands, well-developed seed banks 

can emerge when conditions permit and sites may be colonized by adjacent vegetation 

or propagules from elsewhere. Because the germinant to seedling stage may be the 

most vulnerable in the life history for most species, an understanding of each plant’s 

requirements for germination and survival (termed the “regeneration niche” by Grubb 

[1977]) is particularly important in managing site hydrology to encourage recruitment 

of desirable species.

The requirements for establishment of many wetland and riparian species are understood, and quantifications of conditions that increase the probability of survival have 

been derived from tracking the fates of individuals in field studies (Houle 1994, Johnson 

2000, Dixon 2003) and through experimentation (Horton and others 1960, Scott and 

others 1993, Segelquist and others 1993, Horton and Clark 2001).

Along rivers, flow-related factors such as fluvial disturbances create open patches 

for establishment of colonizing species, wetting of soils, and deposition of sediment. 

Fluvial processes may create and maintain open sites for recruitment through scour and 

deposition associated with the meandering processes, braiding, bar formation, overbank 

flooding, and lateral and vertical deposition of sediment (Scott and others 1996, Cooper 

and others 2003a). Whereas generalist recruitment strategies may enable some species 

to establish successfully over a range of conditions, many pioneer species in wetlands 

and riparian areas are reproductive specialists, requiring open substrate and specific 

moisture requirements for successful recruitment (e.g., the family Salicaceae) (Karrenberg and others 2002). The rate of surface water and groundwater level decline during 

initial establishment has been shown to be important for a range of species (Hughes and 

others 1997, Dixon 2003, Rood and others 2007).

Though there are few formal rules for linking the regeneration niche to flow regime 

along rivers, the wealth of information about cottonwood autecology, specifically recruitment, has led to the development of some very useful tools for managing river flows. 

One such tool is the “recruitment box” model (Mahoney and Rood 1998) (Figure 5-7). 

Figure 5-7. Recruitment box model developed by Mahoney and 

Rood (1998). The model incorporates the optimal timing and rate 

of drawdown of river stage-groundwater for cottonwood seedlings, 

but the concept is applicable to other species that are dependent on 

declining water table and that disperse their seeds in association 

with specific hydrograph attributes.
USDA Forest Service Gen. Tech. Rep. RMRS-GTR-282. 2012 79

The model formalizes relationships between cottonwood root growth rate and surface 

and groundwater regime. The model integrates the timing of cottonwood seed release, 

the range of river stages that define the optimal position on the floodplain for seedling 

survival (high enough on the floodplain to avoid scour by subsequent floods; low enough 

to avoid drought stress), and the rate of stage/groundwater decline suited to maximum 

cottonwood seedling root extension rates (~2.5 cm/day). Along flow regulated rivers, 

the model can be used to manage hydrologic regimes (magnitude of peak, timing of 

peak, and rate of stage decline) to enhance cottonwood seedling survival.

The recruitment box model has been widely used to aid in the design of flow regimes 

to enhance recruitment for riparian forest restoration (Rood and others 2003, Rood and 

others 2005). The model assumes that river stage and alluvial groundwater decline are 

closely coupled, which may not be the case along gaining river reaches, in fine textured 

substrate, and in sites with complex substrate stratigraphy (Cooper and others 1999, 

Merigliano 2005). Seedlings in well-drained soils may be more vulnerable to rapid 

groundwater decline than those growing in finer textured substrate (Cooper and others 

1999).

Although this elegant model was developed for cottonwood in western North America, 

the concept has also been applied to Salix spp. (riparian willow; Rood and others 2005)

and could be readily transferable to other sexually reproducing species with specialized 

recruitment traits. The model could also be used to prevent invasion by undesirable species by decoupling the timing of seed release from the availability of suitable habitat 

(Shafroth and others 1998). This model is not applicable to clonal plants because they 

may reproduce largely asexually, for example Populus angustifolia (narrow leaf cottonwood) and Salix exigua (sandbar willow).

Of course, the survival of an individual or patch of individuals depends on other 

factors such as current and future conditions of the geomorphic features upon which 

they are deposited and germinate. Factors such as light availability, nutrient availability, 

substrate texture (and water holding capacity), presence of and competition with other 

individuals or species, herbivory, and flow related disturbance such as flooding and 

scour or burial are all important in determining the success of establishment (Francis 

and Gurnell 2006). However, the availability of water in appropriate amounts and at 

the correct times for individual species or groups of species increases the likelihood of 

their survival.

Growth and maintenance

Once individuals have successfully passed from seedling to juvenile stage, hydrologic 

processes (e.g., water availability) continue to be a determinant of growth, long-term 

survival, and mortality for wetland and riparian plants (Stromberg and Patten 1990, 

Cooper and others 2003a). As mentioned above, physiological and morphological attributes (e.g., water status, photosynthesis, and transpiration) of riparian plants tend 

to be the most sensitive to changes in flow regime over short time scales (Table 5-1). 

Physiological responses to changing hydrologic conditions can occur over the period of 

several hours and can have long-term repercussions for the morphology and fitness of 

the individual. Water stress and reduced transpiration can result in lower growth rates, 

which in herbaceous species can be measured during the growing season, and in woody 

vegetation can be measured over multiple seasons.

Measurements of incremental growth such as annual branch growth and tree ring 

width has been very effectively modeled as a function of total annual flow volume or 

specific streamflow attributes along streams (Stromberg and Patten 1996, Disalvo and 

Hart 2002) (Figure 5-8). Such relations can be used to set targets for total annual flow 

volume to promote some desirable or acceptable growth rate of trees and to avoid volumes that inhibit growth.
80 USDA Forest Service Gen. Tech. Rep. RMRS-GTR-282. 2012

Individual distributions

Flow-related variables have universally been found to be strong predictors of species 

distributions in wetlands and riparian ecosystems (Franz and Bazzaz 1977, Shipley and 

others 1991, Merritt and Cooper 2000). Species are sorted along elevation and microtopographic gradients according to differences in their response to flooding regime (Franz 

and Bazzaz 1977, Auble and others 1994). When related to environmental conditions 

(e.g., soil moisture, soil texture, nutrients, depth to water table), the present distributions 

of individual species on a landscape can aid in understanding the range of conditions 

under which they can survive. It is also useful to examine where they do not occur 

as that may indicate that the plants are stressed or outside of their tolerance for some 

resource or stressor. The niche of a species may be represented as a multidimensional 

Figure 5-8. Radial growth of cottonwood (Populus trichocarpa) as a function of streamflow for 

three stream types: (A, B) diverted streams in wide, alluvial valleys; (C, D) free-flowing streams in 

wide, alluvial valleys; and (E, F) free-flowing streams in narrow, confined valleys. Regression lines 

and 95 percent confidence intervals are indicated. From Stromberg and Patten (1996).
USDA Forest Service Gen. Tech. Rep. RMRS-GTR-282. 2012 81

representation of biotic and abiotic factors to which the population responds. Fitting a 

distribution or function to presence-absence or abundance data of the species along an 

environmental gradient (e.g., flow related) or multiple gradients is a way to simultaneously test a hypothesis about its niche and develop a framework for prediction of its 

distribution under changing conditions (Franz and Bazzaz 1977).

Distributions or functions are fitted to plot-level or site-level presence-absence or 

abundance data most commonly without regard for stage of development in plants 

(“holistic” approach), as opposed to examining the characteristics of different age or 

size classes. If plants are distributed linearly along a gradient (usually because only a 

portion of the gradient was sampled), linear or log linear regression can be used to fit 

a curve to the abundance data. If presence-absence data are being analyzed, probit or 

logit (logistic) regression is used to model probability of presence. If a wide gradient 

is sampled and species are unimodally (bell shaped or normally) distributed, Gaussian 

regression is usually used to model abundance data, and polynomial logistic regression 

is used to model probability of occurring along the gradient(s). The steps in the process 

of fitting Gaussian (normal) curves to species abundance data involves:

(1) Plotting species abundance data along a hydrologic gradient comprised of hydrologic values for each corresponding vegetation sample. Hydrologic variables may 

include soil moisture, flow duration, flood frequency, depth to groundwater, or 

any number of factors that might explain variability in distributions of individual 

plant species;

(2) Fitting an appropriate curve (model) to the data (Figure 5-9); and

(3) evaluating the fit of the curve to the data.

Such species distributions provide insight into the breadth of the species’ realized 

niche (Hutchinson 1957), indicate its “ecological amplitude” (affinity and tolerance 

to resources and stressors), and its environmental optima along a hydrologic or other 

gradient(s).

Curves may be fitted in any plotting software or statistical program (e.g., SAS, 

SigmaPlot, R) or with curve fitting add-ons for Microsoft Excel. If model fit statistics 

(r-square, log likelihood, Chi square goodness of fit, etc.) indicate that the model adequately describes the data, these models may be used to predict abundance in unmeasured 

sites or under modified conditions. General methods for fitting models are reviewed by 

Jongman and others (1995).

Figure 5-9. Probabilistic species response curves. 

The independent variable may be any of a number of 

flow-related gradients such as soil moisture, depth to 

groundwater, inundation duration, flood frequency, or 

any number of plant-relevant hydrologic variables. Different lines represent different species.
82 USDA Forest Service Gen. Tech. Rep. RMRS-GTR-282. 2012

Community Analysis

An alternative to probabilistic modeling of each species is indirect and direct gradient 

analysis using a variety of ordination techniques (Jongman and others 1995). Ordination 

can reduce the dimensionality of the data so that plots are arrayed in a way that may be 

plotted in two or three dimensions. Vegetation plots are arrayed in the ordination space 

so that compositionally similar plots are closer together and those that are less compositionally similar are further apart. Principal components analysis (PCA), detrended 

correspondence analysis (DCA), non-metric multidimensional scaling (NMDS), redundancy analysis (RA), and canonical correspondence analysis (CCA) are all options for 

reducing multivariate species composition data from many plots into fewer dimensions 

for analysis and visualization. DCA and CCA assume unimodal (Gaussian) distributions 

of species and array these distributions along axes either defined by combinations of the 

species (DCA) or constrain the ordination axes to be linear combinations of measured 

environmental variables (CCA). PCA may be used when only a portion of a gradient 

is sampled and the species are distributed linearly along the portion sampled (Figure 5-10). When assumptions regarding multivariate normality are violated, NMDS 

may be used as a non-parametric alternative.

Regressing flow-related variables against PCA or DCA axis scores can reveal which 

variables the species are collectively organized along and may provide an indication of 

which flow-related variables best account for variation in community structure (Vanderijt 

and others 1996). By constraining the ordination axis scores to be linear combinations of 

measured environmental variables, CCA also provides tools for identifying the principal 

flow-related variables describing species distributions (Figure 5-11). An assumption of 

CCA is that all important variables have been included in the model. These techniques, 

which have become widely used in community ecology, bridge the gap between analyzing individualistic responses of species and examining patterns in community structure.

Figure 5-10. Models fitted to species abundance and presence-absence data 

along a hydrologic gradient (single species models). Multiple species plots are 

from ordinations and the first two ordination axes are shown. From upper left in 

a clockwise direction: linear regression, logistic regression, principal components 

analysis, detrended correspondence analysis, polynomial logistic regression, 

and Gaussian function.
USDA Forest Service Gen. Tech. Rep. RMRS-GTR-282. 2012 83

Figure 5-11. Plots of the first two axes from detrended correspondence analysis of vegetation 

samples taken in riparian areas along the free-flowing Yampa River and the regulated Green River 

in Colorado and Utah, respectively. The top plot (A) illustrates a successional sere dominated by 

cottonwood forest with gradual species turnover along the free-flowing river and an abrupt transition between dry uplands and fluvial marsh along the regulated river. The lower plot (B) illustrates 

the distribution of several species (indicated by six letter acronym) arrayed along an inundation 

duration gradient. From Merritt and Cooper (2000). 

A

B
84 USDA Forest Service Gen. Tech. Rep. RMRS-GTR-282. 2012

PCA and NMDS may be performed in many statistical programs, however DCA and 

CCA are specialized and are only available in community analysis software programs 

such as PC-Ord (http://home.centurytel.net/~mjm/), CANOCO (http://www.pri.wur.nl/

uk/products/canoco/), and Multi-Variate Statistical Package (http://kovcomp.com/mvsp/

index.html). The vegan package of the statistical computing software package R can 

perform many of the analyses outlined above, including DCA, CCA, PCA, and NMDS 

(available for free download at http://cran.r-project.org/web/packages/vegan/index.html).

The vegetation data necessary to perform analysis by any of these approaches is typically in the form of plot numbers (unique identifier) in the first row and species names 

(typically acronyms) as row headers with individual cells in the matrix containing an 

abundance value (e.g., percent cover) for each species. If the species is absent from a 

particular plot, a zero value is entered (Figure 5-12).

A wide range and combination of flow-related variables may be used in gradient 

analysis to define the niche space of each species at a site or to include in ordination. 

Such applications of direct gradient analysis assume that the relationships between the 

environmental gradient and the distributions of plant species are inherent attributes of 

the species and do change as a result of altered hydrology. Quantitatively relating flow 

Figure 5-12. Plot by plant species matrix in Microsoft Excel for input to many statistical analysis software programs.
USDA Forest Service Gen. Tech. Rep. RMRS-GTR-282. 2012 85

attributes to response of individual species provides a continuum of probable change. 

Collectively, the flora in a riparian area may contain a range of species with numerous 

combinations of tolerances and requirements, some of which are in direct conflict. 

Niche-based modeling quantifies this and provides an estimate of how different flow 

regimes in different years could provide for the requirements of a range of species. Another important consideration of niche-based modeling is that the response of different 

species to changes in flow regime varies widely. Short-lived species such as annuals 

could respond on the scale of a single season, but longer-lived species could require 

decades or even centuries to completely respond. Furthermore, the predictions from 

niche-based models only provide an estimate of the probability of change. A variety of 

other factors (fire, herbivory, competition, disease, fluvial disturbance) influence the 

distributions of species, and if not explicitly incorporated into models, these factors 

increase the uncertainty of predictions (Auble and others 2005). These models provide 

a probabilistic view of responses. These probabilities of change may be used as a risk 

assessment to inform the development of limits on permissible hydrologic alteration.

Managing for single species is rarely advisable; however, individually modeling a 

large number of species can be problematic. Direct gradient analysis has been applied 

not only to probabilistic modeling of individual species and groups of individual species but also to modeling of plant associations (communities) and cover types, as will 

be discussed later in this chapter.

Populations

Often, river management plans are tailored to keystone, indicator, or umbrella species, or species of special concern (e.g., threatened or endangered) (Lambeck 1997). It 

is important not only to know the distribution of the species across the landscape, but 

also to understand how the species is performing (e.g., recruitment and overall fitness) 

at the population level. This can be accomplished through characterizing the population 

structure using age-class distributions or modeling populations using structured modeling.

Examining structure (age- or size-class distributions) of a population is helpful in 

determining what life-stage is most affected by changes in flow regime. Age- or sizeclass distributions, evidence of successful recruitment, or some functional assessment of 

life-stage can yield significant insight into the structure of the population and can provide 

an indicator of “bottlenecks” that may be negatively affecting one or more life-stages 

(e.g., recruitment failure). Age-class distributions may also provide insight into eventdriven recruitment events that may be statistically related to hydrologic characteristics 

(Figures 5-13A and B) (Auble and Scott 1998, Birken and Cooper 2006, Rathburn and 

others 2009). Such distributions can be statistically compared between two different 

populations or for a single population to document the population-level response to 

changing environmental conditions.

As mentioned, tolerance of plants to inundation, fluvial processes (scour and burial), 

anoxia, and drought vary as a function of developmental stage for many species adapted 

to riverine environments (Smith and others 1998, Friedman and Auble 1999). In riparian 

areas, many colonizing species germinate and establish on freshly deposited alluvium 

near the channel, whereas adults persist as channel migration and floodplain abandonment cause local soils to become more desiccated over time. Thus, a species may be a 

specialist requiring specific conditions to establish and exhibit more generalist traits during 

later stages of development. The better we understand the specific relationships between 

flow-related processes and the survival and mortality of plants at different stages, the 

greater an opportunity we have for modeling populations and examining differences in 

population growth rates in response to different combinations of environmental factors. 
86 USDA Forest Service Gen. Tech. Rep. RMRS-GTR-282. 2012

Figure 5-13. Age class distribution for alder (Alnus incana, A) and western red cedar (Juniperus scopulorum, B) upstream and downstream from a dam along the North Fork Cache la Poudre River in Colorado 

(Rathburn and others 2009). These distributions indicate that size class distributions of alder are similar 

upstream and downstream from the dam. In contrast, there is a wide distribution of ages of western red cedar 

(an upland species) in riparian areas downstream from a dam compared to the narrow distribution of older 

individuals upstream from the dam. The divergence of upstream and downstream population structures is 

accentuated by the arrows. This is one indication that regulated flows may be enabling encroachment of 

western red cedar into riparian areas downstream from the dam.

A

B

Though formal approaches for modeling and projecting population dynamics of species 

through time may be very instructive, the techniques are mathematically intensive and 

are beyond the scope of this guide (Caswell 2001, Lytle and Merritt 2004).

Plant Communities

Hydrologic alteration often results in shifts in predictable community-level attributes 

of riparian vegetation, including species richness and plant community composition 

(Nilsson and others 1991, Jansson and others 2000, Merritt and Cooper 2000). Collective 

attributes of the community (e.g., richness, diversity, cover and biomass) are linked to 

hydrologic attributes of rivers and may respond in predictable ways to specific hydrologic 
USDA Forest Service Gen. Tech. Rep. RMRS-GTR-282. 2012 87

alterations (Figure 5-11) (Nilsson and Svedmark 2002, Lite and others 2005, Birken 

and Cooper 2006). The ordination techniques that were previously described may be 

very useful in examining shifts in communities through time, comparing unimpacted 

to impacted conditions, and providing insight into relationships between hydrological 

variables and community attributes (Figure 5-11). In addition, there are a variety of 

other techniques for evaluating community attributes: examining differences in species 

richness, categorizing species according to some shared trait or common functional 

attribute, comparing relative proportions of species to a reference stream or reach, and 

examining similarity and dissimilarity in species composition between populations of 

interest. Many of these may be used in conjunction with ordination, to evaluate specific 

questions, and to provide complementary information.

Species richness (number of species) may be compared by evaluating average plotlevel richness between populations of interest using t-tests to compare two groups or 

analysis of variance ANOVA for comparing more than two groups. When statistical 

assumptions for t-tests and ANOVA are not met (e.g., data are normally distributed), 

non-parametric tests such as Mann-Whitney U test and Kruskal-Wallis ANOVA, respectively, may be preferable.

Because number of species increases as a function of area sampled, care must be 

taken that the number of plots and their dimensions are the same between the populations being compared or that adjustments are made to account for differences in the 

area sampled. One such adjustment is to divide species richness in each plot or sample 

unit by the natural logarithm of the collective area of plots and to then compare areaadjusted richness, as previously described. Another method is to estimate the richness 

of an area by fitting species accumulation curves to the plot-level data from the area. 

Species area curves may be fitted using bootstrapping techniques in software such as 

Primer-E (http://www.primer-e.com/) or Estimate-S (http://viceroy.eeb.uconn.edu/estimates). Total species richness between sites may then be compared using Chi-square 

tests. Another simple method for comparing sites with different numbers of plots is to 

randomly select a subset of plots from the site that has the most plots so that identical 

numbers of plots are being compared in an unbiased way.

In addition to comparing richness, community biodiversity may be compared using 

one of many biodiversity indices, which account not only for the number of species 

but the evenness of species as well. If average plot-level diversity is being compared, 

different numbers of plots may be used, but they must be of the same size. If total biodiversity is being compared, similar area (cumulative area of plots) must be sampled, 

as when comparing richness.

Another commonly used approach to compare community attributes is to classify 

species into functional groups based upon some shared trait or function (see Merritt 

and others 2010). The relative proportions of native to non-native species may also be 

compared. The life form of species may be grouped and compared between sites, treatments, or over time. For example, the relative proportions of trees; shrubs; herbaceous 

dicots; and grasses, sedges, and rushes may be compared, as these life forms and groups 

may respond in different ways to hydrologic alteration. Other functional grouping variables that could be used for community comparison are wetland indicator status (Reed 

1988), Raunkiær life form (plants classified by where the perennating buds are stored 

on the plant) (Crawley 1986), Grime’s (1977) plant strategy categories (competitor, 

stress tolerator, and disturbance-adapted), or any number of other relevant functional 

characteristics. For example, reduction in the relative proportion of obligate wetland 

species relative to upland species may provide a compelling quantitative measure of 

the effects of groundwater pumping or wetland draining on wetland plant communities. 

Lite and others (2005) classified plants into categories associated with their affinities 

to various depths to groundwater and reproductive traits (e.g., hydromesic perennial, 
88 USDA Forest Service Gen. Tech. Rep. RMRS-GTR-282. 2012

hydromesic annual, xeric perennial, and xeric annual). Using the Raunkiær system of 

categorizing plants according to the position of buds or regenerating parts of a plant 

(Raunkiær 1934), Nilsson and others (1994) found differences in the traits of riparian 

plant communities between different sites. Communities may be compared for absolute 

or relative proportions of various functional categories using Chi-square tests.

Comparisons in species composition between two different communities or the same 

community before and after a treatment may be made by calculating a matrix of indices 

of community similarity or dissimilarity and comparing average similarity or dissimilarity 

within and between populations (Legendre and Legendre 1998). Such matrices may be 

constructed quickly from a plot-species matrix (Figure 5-12) using statistical programs 

(e.g., SAS) or specialized community analysis software such as Primer-E, MVSP, or R. 

Community similarity can be compared within and between populations using standard 

measures (e.g., Jaccard’s measure, which uses only presence-absence; or the Bray-Curtis 

similarity coefficient, which accounts for abundance or others) (Legendre and Legendre 

1998). Species accounting for differences may then be identified. Statistical comparisons 

may be made using t-tests or ANOVA to compare average similarity within and between 

populations. A more formal comparison may be made through performing an analysis of 

similarities (ANOSIM) (Legendre and Legendre 1998). ANOSIM has been widely used 

for testing hypotheses about spatial differences and temporal changes in assemblages 

and for detecting environmental impacts (Renöfält and others 2007). In comparing 

the degree of change from natural conditions anticipated for plant communities under 

various reservoir operation scenarios, Franz and Bazzaz (1977) predicted that vegetation dissimilarity would range from 16 to 30 percent for three different plans, and the 

authors recommended a flow regime that minimized departure from natural conditions. 

Specialized statistical software is available for performing ANOSIM using similarity 

indices chosen by the user (e.g., Primer-E).

Plant communities may also be compared after classifying them into cover types using either subjective classification or more objective classification. Plant communities 

may be objectively classified using divisive or agglomerative clustering using statistical 

software or specialized community analysis software such as PC-Ord, Two-Way Indicator Species Analysis (TWINSPAN; http://www.canodraw.com/wintwins.htm), Primer-E, 

MVSP, or R. In riparian areas and wetlands, plant associations (dominant cover types) 

show strong affinities for specific hydrologic attributes such as inundation duration 

(Franz and Bazzaz 1977, Auble and others 1994, Friedman and others 2006) and depth 

to groundwater (Rains and others 2004, Camporeale and Ridolfi 2006). In addition to 

examining individualistic responses of species to inundation duration, Franz and Bazzaz (1977) examined community response by analyzing probable changes in vegetation 

cover types as a whole. They used individual species response curves to predict the 

probability of occurrence of species in communities under various flow scenarios and 

then used dissimilarity indices to examine percent compositional departure from natural (reference) communities. Discriminant function analysis or Bayesian discriminant 

analysis may be used to classify plant cover types into independently determined cover 

types as functions of multiple environmental variables (Szaro 1990, Castelli and others 

2000). These functions may then be used to predict shifts in cover type as a function of 

changing abiotic variables (Rains and others 2004).

Other methods of characterizing vegetation based upon overall stand attributes are: 

examining biomass, vegetation volume, and stand physical structure (Stromberg and 

Patten 1990, 1991; Stromberg and others 1993). These attributes can be regressed against 

hydrologic variables and the relationships used to estimate stand attributes in response 

to flow alteration, extraction scenarios, or climate change. One advantage of these 

simple approaches is that a full range of responses are modeled, enabling an evaluation 

of trade-offs between flow alteration and measurable riparian or wetland conditions.
USDA Forest Service Gen. Tech. Rep. RMRS-GTR-282. 2012 89

Conclusions

A variety of methods are available for evaluating vegetation and its relationship to 

hydrologic conditions. Rather than a comprehensive review of the many methods that 

have been developed by plant ecologists over the past century, an overview of what we 

perceive to be some of the simplest and most effective approaches has been presented. 

Most of these approaches do not require a tremendous mathematical background or 

specialized skills to use, yet the approaches enable users to utilize the vegetation and 

hydrologic data gathered using the techniques outlined in other chapters of this guide to 

address specific questions, test specific hypotheses, make formal comparisons between 

sites or treatments, track trends over time, and develop predictive ability to inform 

management decisions.

The choice of one or a combination of organizational levels of plants (individual, 

population, community, or functional grouping) will hinge upon the management questions at hand. In some cases, a combination of sensitive and robust measures will be 

necessary (Table 5-1) to fully evaluate the causes of change or to project change under 

various flow alteration or water extraction scenarios. Tailoring the data collection and 

analyses to conform to management questions, legal mandates (e.g., threatened or endangered species and guidelines in land management plans), or a particular ecosystem type 

or set of stressors requires a basic understanding of the range of approaches presented 

here and some clear management objectives for species or communities of interest. One 

instructive way to formulate which approaches to apply is to examine examples from 

the literature and look for similarities to issues at hand. Table 5-2 provides a review 

of the approaches presented here on systems ranging from fens and small streams to 

large rivers, reservoir margins, and bottomland swamps. This review, examination of 

relevant references, and a basic foundation in the statistical techniques suggested here 

will provide tremendous opportunities for quantitative evaluation of plant-hydrology 

relations for management of wetland and riparian ecosystems of management concern. 

Some excellent references for additional explanation of the techniques presented in 

this chapter are: Manly 1994, Jongman and others 1995, Legendre and Legendre 1998, 

McCune and Grace 2002.
90 USDA Forest Service Gen. Tech. Rep. RMRS-GTR-282. 2012

Table 5-2. Examples of studies examining riparian vegetation at individual, population, community, and guild levels. Hydrologic variables used 

to model vegetation attributes, statistical method, and assumptions of the various studies are given. From Merritt and others (2010a).

Model level Citations

Hydrologic 

variable/s tested

Best hydrologic 

variables

Vegetation 

attribute Analysis tool Assumptions Locations

Individual/

Establishment

Rood and 

Mahoney 1993; 

Mahoney and 

Rood 1998

Timing of peak, 

rate of stage decline 

All Seedling survival Recruitment box 

model

Static channel 

geometry, coarse 

textured substrate

Oldman River, 

Alberta, Canada

Individual/

Maintenance

Busch and 

Smith 1995; 

Cooper and 

others 1999; 

Scott and others 

1999

Depth to 

groundwater

Depth to 

groundwater

Xylem pressure 

potential, leaf 

thickness, leaf 

area, canopy 

volume, annual 

branch growth

Logistic 

regression, 

linear regression

Static channel 

geometry

Bill Williams and 

Coloraro R.; AZ, 

USA; eastern 

CO, USA; Green 

R., UT, USA

Individual/Cover 

types 

King and others 

1998

Water level Water level Stress, mortality, 

and regeneration, 

tree relative 

importance values

Probit analysis Ouachita and 

Saline R., AR, 

USA

Population Lytle and Merritt 

2004; Grifith and 

Forseth 2005; 

Smith and others 2005 

Distributions of 

floods, droughts, 

timing of peak, 

rates of change 

in flow; timing of 

flood, timing of 

drawdown

Distributions of 

floods, droughts, 

timing of peak, 

rates of change 

in flow; timing of 

flood, timing of 

drawdown

Population growth 

rate, stage-based 

population growth 

rate, sensitivities, 

elasticities, 

variability in 

population growth 

rate, aerial cover 

of lfe-stages

Stochastic 

structured/ 

matrix modeling

Quasi-equilibrium 

channel

Yampa R., CO, 

USA; Illinois R., 

IL, USA 

Population Clipperton and 

others 2003

Flow exceedance 

probability 

n/a Populus 

recruitment, 

growth, health 

(qualitative)

Qualitative 

coupling of 

requirements 

for recruitment, 

growth, and 

maintenance

Saskatchewan 

R. basin, Alberta, 

Canada

Population Pearlstine and 

others 1985; 

Phipps 1979

Depth to groundwater, flood frequency, inundation 

duration

Depth to 

groundwater, 

flood frequency, 

inundation duration

Growth, dispersal, 

death, of five tree 

species

Numerical 

modeling

Static channel 

geometry

Santee R., SC, 

USA; White R., 

AR, USA

Community/

Individual

Franz and 

Bazzaz 1977; 

Auble and 

others 1994; 

1998; 2005; 

Friedman and 

others 2006

Flow duration Flow duration Response 

curves of plant 

associations, 

response curves of 

individual species

Numerical 

modeling, 

response curves 

(Gaussian, 

logistic 

regression)

Static channel 

geometry

East-central IL; 

Gunnison R, CO, 

USA; San Miguel 

R, CO, USA

Individual/Stand Stromberg and 

Patten 1990; 

Stromberg and 

Patten 1991

Annual flow 

volume, flow 

volume -1 and -2 

yrs, cumulative 

flow pervious 4 

years, season flow 

volume (Oct-Mar, 

Apr-Jun, 

Jul-Sept )

Annual flow 

volume the year of 

growth

Tree incremental 

growth, canopy 

vigor, mortality 

Linear 

regression

Rush Creek and 

Bishop Ck., CA, 

USA

Individual/

Community

Stromberg 1993 Mean growing 

season flow 

volume, mean and 

median annual 

flow volume, flood 

magnitude 

Growing season 

flow volume, flood 

magnitude

Abundance 

(foliage area, stem 

basal area, stand 

width), species 

richness

Second order 

linear regression

Static channel 

form

Verde R., 

Arizona, USA

Cover types/

Functional 

groupings

Rains and 

others 2004

Depth to 

groundwater, 

flooding

Depth to 

groundwater

Response 

curves of plant 

associations

Numerical 

groundwater 

model 

(MODFLOW), 

Bayesian 

classification

Static channel 

form

Little Stony Ck., 

CA
USDA Forest Service Gen. Tech. Rep. RMRS-GTR-282. 2012 91

Cover types Johnson 1992 Water development Change in riparian 

cover types

Compartmental 

simulation 

model/numerical 

modeling

Missour R., MI, 

USA

Cover types Springer and 

others 1999; 

Baird and others 

2005

Depth to 

groundwater

Woody vegetation 

cover, cover 

seedling 

establishment, 

cover juvenile 

survival habitat

Numerical 

groundwater 

model 

(MODFLOW) 

and conceptual 

vegetation 

model 

Static channel 

geometry

Verde R., AZ, 

USA

Cover types Primack 2000 Inundation duration 

(classes)

Inundation duration 

(classes)

Cover types Cover types Static channel 

geometry

Pere Marquette 

watershed, 

Michigan, USA

Community/

biomass

Camporeale and 

Ridolfi 2006

Stream discharge Stream discharge Probability 

of vegetation 

biomass

Stochastic 

modeling

Hypothetical

Stand characteristicsPerucca and 

others 2006

Distance from river 

(parabolic function 

to represent a 

position between 

anoxic and dry)

Distance from river 

(parabolic function to represent a 

position between 

anoxic and dry)

Biomass Fluid dynamic 

model, river 

meandering 

model, 

numerical 

simulation, 

logistic model

River dynamics 

“induce vegetation 

patterns”

Hypothetical 

(using data 

from SC, USA, 

Pearlstine and 

others. 1985)

Stand 

characteristics

Stromberg and 

others 1993

Depth to 

groundwater

Depth to groundwaterStand biomass 

(leaf area index 

and vegetation 

volume), stand 

structure 

(maximum 

canopy height, 

and basal area), 

leaflet variables 

(primary leaflet 

area, primary 

leaflet length, and 

secondary leaflet 

number), xylem 

water potential

Second order 

linear regression

Hassayampa R., 

San Pedro R., 

Tanque Verde 

Ck., AZ, USA

Cover types/

Functional 

groupings

Toner and 

Keddy 1997

Depth, duration, 

and timing of 

flooding, fraction 

of the growing 

season flooded, 

last day of first 

flood, length of 

the second flood, 

mean depth of 

flooding, number of 

floods per growing 

season, number of 

days of drawdown 

preceding 

midseason floods, 

time of second 

flood

Depth, duration, 

and timing of 

flooding

Presence-absence 

of woody cover 

Logistic 

regression

Static channel 

geometry

Ottowa R. 

Ontario, Canada

Cover types/

Functional 

groupings

Richter and 

Richter 2000

Duration of 

flooding above 

threshold (effective 

discharge)

Duration of 

flooding above 

threshold (effective 

discharge)

Abundance of 

patch types

Numerical 

model 

simulations

Flood driven 

meandering drives 

forest succession; 

channel 

maintenance 

approach

Yampa R., CO, 

USA

Table 5-2. Continued.

Model level Citations

Hydrologic 

variable/s tested

Best hydrologic 

variables

Vegetation 

attribute Analysis tool Assumptions Locations
92 USDA Forest Service Gen. Tech. Rep. RMRS-GTR-282. 2012
USDA Forest Service Gen. Tech. Rep. RMRS-GTR-282. 2012 93

Chapter 6: Case Studies

Case Study I: Mount Emmons iron fen, Crested Butte, Colorado

Introduction and problem statement

The expansion of hard rock mining for molybdenum on Mount Emmons could 

alter the watershed, which supports a unique iron fen located at the mountain base. 

In contrast to bogs, which are rain and snowmelt driven, fens are supported primarily 

by groundwater (refer to Chapter 1). The fen is a State of Colorado Natural Area and 

supports a continuous carpet of acid loving Sphagnum mosses as well as the regionally 

rare carnivorous plant, Drosera rotundfolia (round leaf sundew). Two rare species of 

dragonfly (Leucorhinea hudsonica and Sematochlora semicircularis) are also found 

in the fen. The project goal was to understand the hydrologic and geochemical regime 

that supports the fen.

Background

Many fens in the Colorado Rocky Mountains are supported by groundwater discharge 

from hillslope aquifers. The Mount Emmons fen, located west of the town of Crested 

Butte in the Grand Mesa, Gunnison, and Uncompahgre National Forest, is geochemically distinct because its watershed contains pyrite-rich bedrock. The oxidation of pyrite 

produces sulfide, which in solution, produces sulfuric acid that leaches metal ions from 

rock resulting in acidic and heavy metal-rich water (Cooper and others 2002). These 

ecosystems are termed “iron fens” because dissolved iron is transported to the fen 

where it oxidizes and precipitates onto organic particles to form limonite, or bog iron 

ore deposits. Iron fens are the only wetland ecosystem type in the region with water that 

has a high natural acidity. The combination of peat and limonite accumulation creates 

landforms unique to iron fens, including pools and metal rich terraces (Figure 6-1). In 

addition, iron fens support rare plant species and unique plant communities.

Figure 6.1. Mount Emmons iron fen, Crested Butte, Colorado.
94 USDA Forest Service Gen. Tech. Rep. RMRS-GTR-282. 2012

Approach

This study focused on quantifying the seasonal variation in groundwater levels, 

piezometric heads, water chemistry, and vegetation in the fen while trying to identify 

the water source(s) supporting the fen. Six water table monitoring wells, 1 staff gauge 

in the pond, and 10 piezometers were installed, all into peat soils. Instruments were 

installed in nests consisting of one water table well and two or three piezometers with 

openings at different depths. The location of instrumented sites is shown on Figure 6-2. 

Each water table well and the staff gauge had a continuous water level recorder. After 

installation, well casing lengths and stick up height were measured. Field measures of 

water pH were made by bailing water from monitoring wells. In addition, water samples 

were collected for laboratory chemical analysis of major cation and anion concentrations. Topographic surveying was used to record the fen boundary and the elevation, 

latitude, and longitude of all wells, staff gauges and other topographic features. Daily 

precipitation was analyzed with a logging rain gauge. Correlation analysis was used to 

relate water levels in monitoring wells to each other.

Figure 6-2. Topographic map of Mount Emmons fen. Well 1 (W1), a staff in the fen pond (gray 

area), is located near the pond outlet. Monitoring wells 2 through 7 are also identified. Contour 

interval is 5 m. The fen is 15.1 acres (6.1 ha) in size. 
USDA Forest Service Gen. Tech. Rep. RMRS-GTR-282. 2012 95

Results

Winter precipitation was averaged over the 2002 and 2003 seasons. June and early 

July 2003 were dry, but strong monsoonal flow produced regular rain from late July 

through mid-September. The pond water level varied little during the study period. However, groundwater levels in water table wells varied considerably (Figures 6-3 and 6-4). 

Figure 6-3. Water levels of staff in pond (top) and depth to 

groundwater (ft) in wells 7 (middle) and 5 (bottom) relative to 

piezometers. The figure legend indicates the depth at which 

each piezometer is completed.
96 USDA Forest Service Gen. Tech. Rep. RMRS-GTR-282. 2012

Figure 6-4. Groundwater response at wells 4 and 7 and pond (well 1) and daily precipitation totals 

for summer 2003.
USDA Forest Service Gen. Tech. Rep. RMRS-GTR-282. 2012 97

Most wells had water levels near the soil surface in early summer 2003 due to snowmelt 

recharge of hillslope aquifers. Water levels in wells 2 through 6 remained near the soil 

surface for most of the summer of 2003, while water levels at well 7 declined during 

the summer. Measured head in piezometers was higher than water levels in monitoring 

wells at all sites except well 7, indicating upward vertical gradients (Figure 6-3) and 

groundwater discharge to the soil surface at most sites, including under the pond. In 

addition, groundwater discharging to the surface maintained sheet flow through portions 

of the site. This water had its origin along the northern fen edge. All wells and the pond 

level responded to summer precipitation events, rising after rains and declining during 

rainless periods. This was apparent in September 2003 when a several-week rainless 

period caused groundwater levels to fall (Figure 6-4).

Vegetation of the Mount Emmons fen is dominated by acid-tolerant plant species, 

primarily Sphagnum angustifolium, S. russowii, S. fimbriatum, Carex aquatilis, Carex 

utriculata, Betula glandulosa, Drosera rotundifolia, Vaccinium scoparium, Calamagrostis 

canadensis, Pinus contorta, and Picea engelmannii (vascular plant species nomenclature 

follows Weber and Wittmann [2001], and bryophyte nomenclature follows Crum and 

Anderson [1981]). The western portion of the fen is a water track with sheet flowing 

water and supports a monoculture of Carex aquatilis. The area just west of the pond and 

extending north through the center of the fen has an open overstory of Picea engemannii

and Pinus contorta with an understory of Carex aquatilis or Calamagrostis canadensis. 

The water track on the eastern side of the fen, which flows into the pond, has numerous small, unvegetated pools with vegetated strings between the pools. Carex aquatilis

is the main sedge in these areas, and small populations of Drosera rotundifolia occur, 

especially near wells 3 and 5.

Surface and groundwater flow was from north to south at all times during the study 

period due to the steep topographic and hydrologic gradient that controls surface and 

groundwater flow direction (Figure 6-5). Well 1, the pond staff, was most closely correlated with well 2, which occurs west of the pond, but it was poorly correlated with 

other wells (Table 6-1). Well 4 was highly correlated with wells 3, 5, 6, and 7.

Surface water and shallow groundwater sampled from water table wells were highly 

acidic (Figure 6-6), particularly in well 6. Groundwater discharged and flowed south 

down the limonite water track and into the pond. The pond water (well 1) had a pH 

similar to wells 4 and 5. The three most westerly wells—2, 3, and 7—had higher pH 

than other waters during the fall of 2002. Wells 2 and 7 had similar pH values on 1 July 

2003, while the pH of well 3 dropped to 3.9. The water in piezometers had pH greater 

than 6.0, even beneath the pond or shallow groundwater (Figure 6-7). Thus, two waters 

of distinct pH and likely chemical content meet within the fen, and yet it is the acid 

water of the springs fed by the Mount Emmons pyrites that controls the surface water 

and shallow groundwater chemistry and that facilitates the presence of acid loving and 

acid tolerating biota as well as the formation of limonite landforms.

These data suggest that the northwest portion of the fen received the most acid water 

and that acid concentration decreased by an order of magnitude in the groundwater 

flow system to the west (near well 2) and by two to three orders of magnitude in the 

water beneath the fen. Thus, the acidity of water varied spatially, and acid concentration 

varied by approximately 1000 times between water in well 6 and water in the deepest 

piezometer at well 6. The water at all sites was dominated by calcium and sulfate ions. 

Sulfate likely originated from the oxidation of pyrite (FeS). There was no detectable 

HCO3 or NO3 in any water sample.
98 USDA Forest Service Gen. Tech. Rep. RMRS-GTR-282. 2012

Figure 6-5. Topographic map (contours are 5 m) of Mount Emmons fen with arrows showing principal surface and groundwater flow directions.

Table 6-1. Correlation coefficients (r) between monitoring wells and 

pond for 2003. Each row and column represents a well, 

and input data are depth to water table on each measurement date. 

2 3 4 5 6 7

1 0.558 -0.069 0.086 0.268 0.187 0.131

2 0.022 0.167 0.258 0.348 0.281

3 0.654 0.339 0.608 0.283

4 0.647 0.763 0.614

5 0.426 0.467

6 0.637
USDA Forest Service Gen. Tech. Rep. RMRS-GTR-282. 2012 99

Figure 6-6. Surface water pH at pond (well 1) and six wells (wells 2-7), 

Mount Emmons fen.

Figure 6-7. pH values for surface water or shallow groundwater 

(lower pH value to left) and piezometer water (higher pH value to right) 

at wells 3, 1, and 6.
100 USDA Forest Service Gen. Tech. Rep. RMRS-GTR-282. 2012

Discussion

Groundwater discharging from the base of Mount Emmons produces surface sheet 

flow and groundwater flow that perennially saturates the fen. Water levels remained 

relatively stable at most sites, suggesting that a large volume of groundwater flows 

through the fen. Because the fen has been accumulating peat for more than 8000 years 

(Fall 1997), it is likely that hydrologic processes have been relatively intact for a long 

time. Late summer rain recharges hillslope aquifers, resulting in short-term increases 

in groundwater levels. The fen’s watershed is large and complex with both short and 

long flow paths, which is indicated by perennial groundwater flowing through the fen 

during the summer of 2002, even under extreme drought conditions.

Perennial groundwater inflow is critical to drive hydrologic and geochemical processes that lead to peat formation. In addition, Mount Emmons fen is geochemically 

and ecologically unique. The acidic water is produced from oxidizing pyrite and veins 

of pyrrhotite, another iron sulfide mineral, which is common in areas of contact metamorphism. These rocks surround a molybdenum ore body on Mount Emmons. Acidic 

water produces the unique hydrologic and geochemical environment and an ecological refugium for Drosera rotundifolia, Sphagnum angustifolium, Betula glandulosa, 

and other acid-loving species. These species are dependent upon the perennial flow of 

acidic water. It is critical to understand that groundwater with pH greater than 6.0 is 

present beneath the fen and has sufficient hydraulic head to reach the peat body. If the 

flow of acid water was reduced, the alkaline water could dominate fen geochemistry, 

resulting in the loss of acid-tolerant taxa with no potential for replenishment (Cooper 

and others 2002).

Key methodological approaches used in this study include the use of water table well 

and piezometer nests and analyzing water for pH and chemical content. The pond water 

level is controlled by groundwater inflow and sheet flow, but its level varies little over 

time and is not representative of the natural variation in groundwater inflow within the 

fen. Long-term protection of this fen will require maintaining groundwater inflows to 

maintain groundwater levels throughout the fen, and the water must have the natural 

range of acidity that has been measured. Groundwater levels should be at or above the 

soil surface in early summer. Water levels may drop during the summer, although rarely 

by more than about 50 cm below the soil surface. Groundwater levels typically rise in 

the mid- to late summer due to monsoon rains.

Case Study II: Groundwater pumping in a riparian ecosystem, 

South Platte Park, Littleton, Colorado

Introduction and problem statement

Groundwater can be pumped from alluvial aquifers for agricultural, industrial, or 

municipal uses. In some cases, groundwater is pumped directly from beneath riparian 

zones, resulting in a cone of depression and larger-scale lowering of the water table. 

Groundwater pumping is commonly used to avoid surface water diversions on sand 

bedded streams and where the construction of water diversion structures is difficult.

Most phreatophytes are groundwater dependent and have high water demand during 

hot summer days. Some are highly sensitive to even small changes in water availability. 

For example, Populus deltoides (plains cottonwood) is among the most sensitive tree in 

North America to drought-induced water stress and xylem embolism formation (Tyree 

and others 1994). Embolisms are air bubbles that form in vessels when xylem pressure 

potential lowers to the point where chains of water molecules break and gaseous air 

blocks the movement of water up the vessel. Embolisms make vessels dysfunctional for 

water transport. If enough vessels develop embolisms, the plant will lose a significant 
USDA Forest Service Gen. Tech. Rep. RMRS-GTR-282. 2012 101

proportion of its water transport ability and will suffer leaf or twig dieback or whole 

plant death. While groundwater pumping is generally increasing across the West, we 

still know relatively little about the effects of water table declines on most plant species.

The purpose of this case study was to investigate the effects of groundwater pumping from under the South Platte River floodplain south of Denver, Colorado, on plains 

cottonwood trees. The Centennial Water and Sanitation District (Centennial) had water 

rights along the South Platte River. Instead of building a diversion structure, officials 

chose to install a groundwater pumping system. This portion of the river is within South 

Platte Park, which is managed by the South Suburban Parks and Recreation District and 

the City of Littleton, Colorado. For this project to be permitted by the City of Littleton, 

it was necessary for Centennial to demonstrate that groundwater pumping would not 

harm or kill the cottonwoods along the river.

In the southern portion of this reach, the South Platte River had been mined for gravel 

approximately 30 years prior to this study and had been influenced by a large flood in 

1973. During this flood, the river channel avulsed to the west and the old channel filled 

with sand and gravel, allowing a new cohort of cottonwoods to establish. The former 

mined area had sand and gravel soils, relicts of the floodplain soils. The natural floodplain area had never been mined and had fine-textured soils in the upper 1 m. Large 

populations of cottonwood trees were present on both the mined and un-mined sites, 

providing numerous trees of similar age. The four pumping wells that had been installed 

by Centennial were located in a transect that fortuitously spanned the area between the 

mined and un-mined river reaches (Figure 6-8). Each well was capable of pumping at 

a sustained rate of approximately 30,000 m3/day.

Figure 6-8. Study area location showing drawdown 

contours, pumping wells, 

and plot locations.
102 USDA Forest Service Gen. Tech. Rep. RMRS-GTR-282. 2012

Methods

To determine the potential effects of groundwater pumping on the water table 

configuration, a 30-day pump test was performed in January of 1996, and water table 

drawdown was measured in 18 monitoring wells placed through the study area. The 

drawdown extent and depth (cone of depression) data were used to create a water table 

drawdown map (Figure 6-8). Drawdown was as much as 2.5 m. Based on these initial 

findings, a study was designed to analyze the effects of drawdown amount in each soil 

type (gravel in the mined area and natural soils in the un-mined area) on the riparian 

cottonwoods. Using the water table drawdown map, six study plots, each 600 m2 in 

area and with similar tree density (1000 trees/ha), were chosen to represent deep drawdown (1.5 to 2.0 m), moderate drawdown (0.3 to 0.6 m), and no drawdown (controls) 

in the mined and un-mined substrate areas. Each plot was equipped with a water table 

monitoring well, and water table depth was measured manually at least weekly during 

the study period. One additional deep drawdown plot was established in each soil type 

to test the effects of supplemental water addition (2.54 cm every three days) applied by 

sprinklers as a watering treatment.

Groundwater pumping began on 3 July and ended on 27 July 1996. The depth to the 

water table was measured weekly prior to and following pumping through the entire 

summer, and daily during the pumping period for the six wells in the study plots.

Five cottonwoods that represented the range of tree size in each plot were analyzed 

for their physiological response to the change in water table depth. Xylem pressure 

potential (Ψxp) was measured on one full sun terminal twig on each study tree using a 

Scholander-type pressure bomb during pre-dawn (00:00 to 05:00) and midday (12:00 

to 15:00) periods. Sampling occurred weekly during the pre-pumping period in the 

summer of 1996, and three times each week during the pumping period. Two observers 

estimated percentage of leaf yellowing and senescence on 25 randomly selected trees in 

each plot during the pumping period. Stomatal conductance (gs) was measured using a 

null balance porometer (LiCor LI-1600) on hourly time steps approximately three weeks 

after the pumping ceased to evaluate plant recovery patterns.

The pre-dawn and midday xylem pressure potential data from the six main plots were 

analyzed using multivariate repeated measures analysis of variance (MANOVA) with 

the GLM procedure in SAS (Cooper and others 2003b). The study design followed a 

split plot design with soil type, drawdown depth, and time as the independent variables. 

Three time periods were analyzed: (1) pre-pumping, (2) the first three sample dates in 

the pumping period, and (3) the last three sample dates in the pumping period. Two-way 

ANOVA was used to test the effect of watering on predawn xylem potential in time 

period (3). Regression analysis was used to model the relationship between maximum 

plot water table drawdown and pre-dawn water potentials on 22 July 1996 as well as 

the percent of leaves that yellowed.

Results

The water table depth was 1.5 to 2.5 m belowground in the pre-pumping period. South 

Platte River flows increased in late June and mid-July and caused a rise in the water 

table, particularly in the mined study reach. Groundwater pumping produced a large 

drawdown in the deep drawdown plots and a smaller drawdown in the mid drawdown 

plots, as predicted (Figure 6-9). When pumping ceased, all water tables rose rapidly.

Midday xylem pressure potential (Ψmd) declined during the pre-pumping period as 

summer temperatures increased (Figure 6-10). Pre-dawn xylem pressure potentials 

(Ψpd) declined very slowly during the pre-pumping period and changed little in the 

first two weeks of the pumping period. There were no differences in Ψmd or Ψpd among plots 

in the pre-pumping period. On 15 July, Ψpd in the deep and mid drawdown plots declined 
USDA Forest Service Gen. Tech. Rep. RMRS-GTR-282. 2012 103

Figure 6-9. Depth to water table for all study plots during the prepumping, pumping, and post-pumping periods.

Figure 6-10. Midday (left panel) and pre-dawn (right panel) xylem pressure potentials for the for all study plots 

during the pre-pumping, pumping, and post-pumping periods.
104 USDA Forest Service Gen. Tech. Rep. RMRS-GTR-282. 2012

sharply, while in the control plots and the watered mined plot, Ψpd remained similar to the 

pre-pumping period. The lowest Ψpd occurred on 22 July, and many cottonwood leaves in 

the affected plots turned yellow and eventually fell from the trees due to the development of 

extreme water stress and cavitation of most xylem in twigs. Once leaf yellowing occurred, 

Ψpd rose due to the reduced leaf area and water demand.

Depth of water table drawdown and percent leaf loss were significantly correlated 

with tree Ψpd on 22 July (Figure 6-11). The depth of water table drawdown was linearly 

related to the decline in tree Ψpd and the loss of leaves. At the end of the pumping period, 

Ψpd was higher in watered than un-watered plots at the mined site, but Ψpd was intermediate between what was measured in deep and mid drawdown plots in the unmined 

site. The drawdown reduced soil water availability, which lowered xylem pressure 

potential, caused the development of embolisms, and led to leaf and twig dieback and 

loss. At the end of the pumping period, Ψpd was lower in watered plots, especially in 

the mined plot. In addition, the two watered plots had much lower leaf loss than trees 

in the deep or mid drawdown plots.

Three weeks after the cessation of pumping, Ψxp measured hourly was similar for 

watered and un-watered deep drawdown plots (Figure 6-12). However, trees in the watered plots reached a higher gs and maintained higher stomatal conductance for longer 

time during the day than did un-watered plots. Thus, watered plots maintained a higher 

level of stomatal conductance and, most likely, a higher rate of photosynthesis compared 

with un-watered plots.

Discussion

Groundwater pumping and other hydrologic changes to riparian and wetland ecosystems can produce both short-term and long-term effects on plants, soils, and ecological processes. This experiment demonstrated the short-term effects that can result 

from lowering the water table under riparian cottonwoods. Populus deltoides is highly 

sensitive to reduced water availability; within two weeks, Ψpd declined rapidly, leading 

to leaf senescence, twig death, and some whole branch sacrifice (death). The loss was 

limited because pumping was ceased as soon as these effects were visible or measureable on the trees. The response of trees to the water table decline was not immediate, 

Figure 6-11. Affects of water table drawdown on pre-dawn water potential (left panel) and percent 

leaf loss (right panel) for all study plots.
USDA Forest Service Gen. Tech. Rep. RMRS-GTR-282. 2012 105

likely due to a short increase in South Platte River discharge, which raised river stage 

and groundwater levels as well as soil water storage, which provided suitable water for 

trees for a short period. While runaway xylem cavitation, or embolism formation, has 

been reported in eastern populations of cottonwood, this study demonstrated that under 

natural conditions trees experienced low water potentials (Ψmd readings of -1.8 MPa) 

but were able to recover their water potentials each night. Thus, western populations of 

this tree species are more drought tolerant than eastern populations. Xylem cavitation 

appeared to be caused by the reduction in Ψpd, indicating that plants could no longer 

acquire sufficient water from the soil to recover each night.

Leaf loss was related to the magnitude of water table drawdown. Even a relatively 

modest water table drawdown of 0.3 m decoupled some or most of the tree roots from 

their water source, resulting in leaf death. A deeper drawdown of greater than 1.0 m 

caused significant whole tree stress. Had this drawdown been sustained, many trees 

would have died, as has been reported for other areas (Scott and others 1999).

Application of a relatively small amount of irrigation water allowed trees to maintain 

their water status with little or no apparent cavitation and leaf loss in study area trees, 

even where deep drawdown occurred. This suggests that trees can effectively switch 

from primarily using groundwater to water in upper soil horizons. The effect was more 

obvious in the sand and gravel mined soil study area than in the fine-grained, un-mined 

soil area, likely due to the coarse soils allowing water to percolate more rapidly to plant 

roots and because these soils supported fewer herbaceous plants.

Figure 6-12. Hourly midday water potential (top panel) 

and gs (bottom panel) for watered and unwatered deep 

drawdown plots.
106 USDA Forest Service Gen. Tech. Rep. RMRS-GTR-282. 2012

Case Study III: Marsh hydrology, Great Sand Dunes National Park, Colorado

Introduction and problem statement

Marshes form in basins where seasonal surface water and/or groundwater create periodic deep standing water that supports highly productive plant communities. Marshes 

are among the most important wetlands for supporting migratory birds and amphibians. 

However, marshes are highly sensitive to the volume of surface water or groundwater 

delivery that fills basins each year, and even small changes in water delivery can lead 

to their drying.

Between 1937 and 1995, a complex of more than 100 marshes disappeared from a 

sand dune complex at Great Sand Dunes National Park in Colorado (Figures 6-13 and 

6-14). These changes were documented using vertical air photographs, but the cause 

was unknown. Three overall hypotheses were advanced: (1) sand dune migration during 

a regional drought in the 1950s buried the marshes; (2) regional groundwater pumping 

lowered the water table, leading to their drying; and (3) changes in local hydrologic 

processes led to wetland loss (Wurster and others 2003). These three possibilities were 

investigated using stream flow records, groundwater level measures, natural stable 

isotopes as a tracer of water sources, buried soil seed banks as an indicator of where 

wetland horizons existed, and groundwater modeling.

Figure 6-13. Location of study 

area along Sand Creek, Great 

Sand Dunes National Monument, Colorado.
USDA Forest Service Gen. Tech. Rep. RMRS-GTR-282. 2012 107

Methods

The studied wetland complex occurred within a sand dune field. There was little 

surface runoff due to the high permeability of the sand. Instead, the marshes were fed 

by groundwater. To investigate the groundwater source(s) and seasonal variation in 

water levels, a total of 120 water table wells were installed by hand in and around both 

the marsh complexes that existed during the study period as well as those identified in 

the 1930s air photos, and in transects that extended across Sand Creek (Figure 6-15). 

Staff gauges were installed in Sand Creek as well as in marshes with standing water. 

Aquifer transmissivity (T) was estimated using the stage ratio and time lag methods 

(Ferris 1963). Average T was determined by calculating the time lag between maximum 

water level fluctuations at different wells in the study area. Specific yield (Sy) was not 

directly measured—a value of 0.15 was used. Since the aquifer was nearly homogeneous 

sand, little variance in its estimate would have occurred.

Stable isotope ratios of δD and δ18O in water samples were used to identify recharge 

and flow paths for the marshes. Monthly water samples were collected from rain events 

and surface water in Sand Creek. Groundwater samples were collected from 10 water 

table wells along transect A-A’ and B-B’ (Figure 6-15). Samples were collected using 

standard protocols, stored in airtight vials, and frozen until analyzed; and all wells were 

bailed prior to sample collection. Analysis was conducted using a VG Optima mass 

spectrometer.

Figure 6-14. Distribution of marshes, black polygons, in 1937 and 1995 showing extensive loss 

of the northern marshes.
108 USDA Forest Service Gen. Tech. Rep. RMRS-GTR-282. 2012

A key goal of this analysis was to understand how the unconfined aquifer responded 

to changes in flow of Sand Creek, a potential recharge source for the marshes. Seasonal 

fluctuations in groundwater levels were modeled by comparing water level change in 

monitoring wells under Sand Creek and monitoring wells at various distances away 

from Sand Creek (Wurster and others 2003).

Historical monthly Palmer Drought Severity Index (PDSI) values for the study area 

were obtained from the National Climate Data Center. PDSI can be used to assess the 

severity of wet and dry weather patterns (Palmer 1965). Historical records of mean daily 

Figure 6-15. Location of monitoring wells.
USDA Forest Service Gen. Tech. Rep. RMRS-GTR-282. 2012 109

discharge for several regional streams with long-term records were used to reconstruct 

the flow of Sand Creek, which had discharge data available only from 1994 to 1999. 

All streams were within 20 km of Sand Creek, had similar watershed areas and lithologies, and were at similar elevations. From these data, a rough flow-duration curve was 

constructed for different years and was used to estimate the aquifer response to stream 

flow from 1936 to 1999. The aquifer’s response as measured by the water table elevation was calculated at a point 1500 m from Sand Creek.

A 6-km reach of Sand Creek’s channel was analyzed using historical air photographs 

to determine whether channel form changes occurred that could have influenced groundwater recharge patterns or processes. The former locations of marshes were identified 

in the field using GPS points, and soils were investigated to identify wetland horizons 

with organic accumulations, gleying or mottling, and the depth of burial, if any. Soil 

samples from any buried wetland horizons found during sampling were collected and 

analyzed for percent organic matter by loss on ignition. The soil seed bank was analyzed 

by spreading soils onto trays in a greenhouse where they were watered to maintain 

saturation for six months. Emerging seedlings were identified and counted.

Results

Mottled soil horizons were interpreted as identifying the seasonal water table 

high and were used to identify the former wetland soil surface. This surface was buried 

more than 0.5 m belowground at a few sites, near wells 97, 98, 99. At all other sites, the 

wetland horizons were at the ground surface. Thus, sand burial of the wetland surface 

was not common in the study area. However, the water table measured during this study 

was well below these mottled horizons, indicating that the wetland soils formed when 

the water table was at a higher elevation.

The plant species that germinated from the wetland soils included: Eleocharis palustris (spike rush), Scirpus pungens (three square bulrush), and Juncus arcticus (arctic or 

Baltic rush), all of which are common and dominant wetland plant species in the study 

area. The presence of germinable seeds indicated that the soil horizons investigated 

supported wetland plants during the Twentieth Century and were the wetlands visible 

on the 1930s era air photographs. Percent organic matter was highest in horizons with 

mottles and that contained germinable seed, providing multiple lines of evidence that 

these horizons were wetland soils.

Water table contours indicated that a regional hydraulic gradient exists between 

Sand Creek and the study wetlands (Figure 6-16). The maps presented illustrate conditions when Sand Creek was not flowing (17 Feb 1999) and was flowing (15 July 1999). 

Water table elevation is highest along the Creek and in the northeastern portion of the 

study area. Therefore, the dominant groundwater flow through the sand sheet was from 

the northeast to the southwest.

Groundwater profiles along transects A-A’ (Figure 6-17A) further clarified the strong 

groundwater gradient from Sand Creek toward Elk Springs. The profile at B-B’ (Figure 6-17B) indicated that a substantial groundwater mound forms under Sand Creek 

when it flows, and the mound dissipates during the summer and fall. When Sand Creek 

is flowing, the water table is in contact with the channel bed. Once surface flow ceases 

in this intermittent stream, the water table declines rapidly. The high soil permeability 

(hydraulic conductivity of approximately 10-4 m/s) facilitates groundwater flow from 

the channel area into the sand sheet and toward the wetland basins.
110 USDA Forest Service Gen. Tech. Rep. RMRS-GTR-282. 2012

Figure 6-16. Water table contours in the study area for February (left) and July 

(right) 1999 when the creek is not and is flowing, respectively. Note contour lines 

straight across creek in February and bending downstream in July. This indicates 

that a groundwater mound forms under the creek when it flows. 

Figure 6-17. Profiles A-A’ and B-B’ showing the elevation of the 

water table along a nearly 2500 m long transect on different dates 

in 1998 and 1999.
USDA Forest Service Gen. Tech. Rep. RMRS-GTR-282. 2012 111

Hydrographs from four wells (101, 100, 94, and 93) at increasing distances from Sand 

Creek depict water table maxima increasing in time from September through March 

(Figure 6-18). A graph of the time lag in days of the groundwater maxima in monitoring wells following Sand Creek’s peak flow indicates a nearly linear temporal increase 

with distance from the creek (Figure 6-19). These data suggest that Sand Creek surface 

flows produce a pulse of groundwater recharge that propagates as a wave through the 

sand sheet and supports groundwater flow through the wetlands. Isotopic analysis of 

the δD/δ18O ratio of creek and groundwater indicated that Sand Creek is the source of 

water for the groundwater flow system that supports the wetlands.

Figure 6-18. Sand Creek average daily discharge during 1998 and groundwater 

levels for four wells during 1998 and 1999.

Figure 6-19. Time lag of maximum groundwater high relative to distance 

from Sand Creek. 
112 USDA Forest Service Gen. Tech. Rep. RMRS-GTR-282. 2012

PDSI values for the Twentieth Century indicated that severe drought occurred during 

the 1930s and 1950s and that wetter periods occurred during the 1910s, 1940s, 1980s, 

and 1990s. Analysis of the Sand Creek channel indicated that it narrowed approximately 

50 percent between 1937 and 1995 and that sinuosity also increased during the same 

period. The relict channel boundaries from 1937 could be identified in the field using 

indicators such as large woody debris, cobbles, stream terraces, and cottonwood establishment sites. The difference in elevation of the channel at the time of analysis (1999) 

in 1937 was 2.5 m, suggesting that the channel incised over the last 60-year period, 

leading to channel narrowing and lowering of the groundwater base level.

Discussion

These analyses provided a wide ranging and complex set of studies, from which it 

was concluded that burial by moving dunes could explain only a small fraction of the 

wetland loss. There was no evidence that regional groundwater pumping was connected 

to wetland loss; however, local hydrologic processes could explain most of it. The study 

marshes are fed by groundwater that is recharged during high flow in Sand Creek as a 

result of early summer snowmelt from the Sangre de Cristo Mountains. Surface water 

recharges the groundwater table, building an elevated groundwater mound under Sand 

Creek that dissipates as it flows away from the creek. The groundwater flow produced 

by the dissipating mound takes 200 to 300 days to reach many of the wetland basins.

The soil morphology, organic matter, and soil seed bank analyses all indicated that the 

former wetland soil surface could be identified and was near the current ground surface. 

But the current groundwater table was well below the ground surface. A groundwater 

model that projected the water table for a point 1500 m from Sand Creek using the 

stream elevation in 1937 and in 1995 after 2.5 m of incision occurred indicated that 

the water table in 1995 would be greater than 0.5 m below the level seen on 1937 air 

photographs and that stream incision is the likely cause of wetland loss (Figure 6-20).

Figure 6-20. Groundwater elevation for a point 1500 m from Sand Creek modeled for 

the period 1937 to 2000 using 1937 stream bed elevation (light line) and current stream 

bed elevation (dark line).
USDA Forest Service Gen. Tech. Rep. RMRS-GTR-282. 2012 113

Even though years of high snowpack and Sand Creek runoff occurred during the 

1980s and 1990s, the water table under the sand sheet has not elevated enough to flood 

the wetland basins. The ultimate cause of stream channel change is unknown. It could 

have been caused by cottonwood establishment along the floodplain margin during a 

period of fluvial stability, hydrologically suitable conditions, or fire suppression in the 

San Luis Valley. The trees could have stabilized banks, constrained the channel, and 

caused it to shift from braided to meandering form. The concentration of flow in the 

stable narrower channel may have resulted in incision. Other possible causes are heavy 

livestock grazing in the channel area or several particularly large flow events.

Case Study IV: Instream flow needs to support groundwater and 

riparian vegetation, Cherry Creek, Arizona

Introduction and problem statement

The U.S. Forest Service filed for an instream flow water right in 1999 for Cherry 

Creek, which is a perennial stream on the Tonto National Forest in central Arizona. The 

State of Arizona approved the requested flows (median monthly), which the agency filed 

for to support wildlife habitat, fishery, and recreation. To better understand the relationships among surface flow in Cherry Creek, groundwater across the valley bottom, and 

the riparian vegetation, a study was conducted along Cherry Creek (Merritt and others 

2010b). Conservation of riparian habitat along the creek is important because riparian 

habitats constitute less than 1 percent of the entire landscape, yet they provide a variety 

of unique resources, functions, recreational opportunities, and habitat qualities not found 

in adjacent upland habitats.

Cherry Creek flows from spring-fed canyon reaches into a wide alluvial valley bottom through which the channel loses to the alluvial aquifer flow for most of the year 

(Figures 6-21A and B). The stream supports diverse deciduous riparian forest that is 

comprised of trees such as Populus fremontii (Fremont cottonwood), Salix gooddingii

(Goodding’s willow), Jugulans major (Arizona walnut), Fraxinus velutina (velvet ash), 

and Alnus oblongifolia (Arizona alder).

A B

Figure 6-21. (A) Aerial photograph of the study reach of Cherry Creek, Tonto National Forest, Arizona. (B) Cherry Creek looking 

downstream.
114 USDA Forest Service Gen. Tech. Rep. RMRS-GTR-282. 2012

Methods

Ten water table wells and two well-staff gauges (wells positioned immediately adjacent to the stream) were established along a 0.5-km alluvial reach of Cherry Creek. The 

wells were established in a grid covering much of the valley bottom on both sides of 

Cherry Creek. Elevation at each of the wells was surveyed, and wells were instrumented 

with Onset Hobo data loggers set to record water depth every 15 minutes. One well was 

fitted with a non-submerged pressure transducer and data logger for later barometric 

correction of water levels. Groundwater surfaces were generated by spline fitting a 

surface through measured groundwater depths (Figure 6-22). Vegetation cover types 

were classified from vegetation sampling plots distributed along transects throughout 

the study area. Cover types were modeled as a function of depth to water table at a stable 

low flow along Cherry Creek using discriminant function analysis. Groundwater decline 

was simulated throughout the study area, and levels were used to predict changes in 

vegetation cover types in the study reach.

A physical model for Fremont cottonwood distribution as a function of groundwater 

depth was constructed using the topography-bathymetry coverage, the water table at low 

flow, and measurements of the mean of six cottonwood root depths from excavations 

conducted in the study area. Potential cottonwood habitat (groundwater within rooting 

zone) was modeled as a function of manually simulating a lowering of the water table. 

Detailed topography (±0.01m) and channel bathymetry through the reach was available 

from an associated USGS study (Waddle and Bovee 2009).

Linkages between groundwater elevations and fluctuations and streamflow in Cherry 

Creek were determined through examining hydrographs (stage and discharge) of flood 

pulses and response of groundwater levels at wells across the floodplain, correlating 

daily groundwater fluctuations with fluctuations in discharge at a USGS gauge 15 km 

upstream from the study area, and developing rating curves (stage-discharge relations) 

at the staff gauges.

Figure 6-22. Contour map of water table (purple surface) with 0.1 m 

groundwater contours, water table monitoring wells (blue cross) and vegetation plots (red symbol), and channel (green). Streamflow is from top 

to bottom of frame. The groundwater flow is general trending down valley 

and toward river right (left side of frame). Scale is 1:3000.
USDA Forest Service Gen. Tech. Rep. RMRS-GTR-282. 2012 115

Streamflow in Cherry Creek was related to water status of important riparian tree 

species by measuring pre-dawn and midday water potential using PMS Model 670 

Scholander-type pressure chambers (PMS Instruments, Corvallis, Oregon) in individuals 

located upstream and downstream from a diversion that withdraws 95 percent of the flow 

in Cherry Creek. The relationship between tree fitness (growth rate) and discharge was 

also examined by coring cottonwood and willow, measuring ring widths, and relating 

these widths to specific monthly flow attributes.

Results and conclusions

Riparian tree species were most abundant in areas along Cherry Creek where groundwater was within 2 m of the ground surface, which corresponds reasonably well with 

the average rooting depth measured from excavated roots (1.74 m). Statistical models 

and physical simulation models predicted that incremental decimeter reductions in 

surface water and groundwater levels to 1 m below base level would cause declines in 

cottonwood-dominated riparian forest from a current level of 41 percent of sites sampled 

to 7 percent at an average loss rate of 3 percent per decimeter decline in groundwater 

level from the modeled low flow (Figure 6-23). The model also predicted that shrubdominated habitat would increase from 59 percent to 93 percent with a 1 m decline in 

groundwater levels. At a 2-m decline in groundwater, only 1.8 percent of the riparian 

habitat would be habitable by cottonwood, and the valley bottom would be comprised 

exclusively of shrubland (98.2 percent frequency).

These findings were independently supported by simulation models that determined 

potential cottonwood habitat through modeling the area of the valley bottom with 

groundwater within the average rooting depth of cottonwood over a range of groundwater levels. Potential cottonwood habitat declined 75 percent (from 65 percent to 16 

percent of the valley bottom) with a simulated 1-m decline in groundwater level (Figure 

6-23). Potential cottonwood forest was virtually eliminated at 1.5- and 2.0-m reductions in groundwater below the modeled low flow (reduced to 7 and 3 percent potential 

habitat, respectively).

The models also illustrated that groundwater decline would result in migration of 

the riparian forest-xeroriparian edge nearer the stream channel and a reduction in the 

extent, or complete loss, of riparian forest, depending on the severity and persistence 

of flow-induced groundwater decline.

Reductions in forest cover and tree species diversity were documented along a perennial to intermittent reach caused by a flow diversion (95 percent of flow diverted) as 

well as an additional perennial to intermittent reach where surface water is controlled 

by underlying bedrock. Forest species cover dropped from 62 to 10 percent in comparisons of perennial to intermittent reaches, and shrubs comprised the dominant cover 

type in the intermittent reach.Downstream from the diversion, riparian tree cover in the 

vegetation plots averaged 4.5 percent compared to 23 percent in forest cover upstream.

Flow diversion caused increases in xylem water stress of riparian cottonwood, Arizona 

sycamore, and Goodding willow, but saltcedar individuals were not critically affected 

by flow diversion (refer to Figure 5-6 in Chapter 5). The consequences of surface water depletion and its effect on water availability to trees included: diminished cover of 

native riparian trees, and higher cover of xerophytic (drought-tolerant) desert shrubs 

(including non-native saltcedar) along the flow-diverted reach.
116 USDA Forest Service Gen. Tech. Rep. RMRS-GTR-282. 2012

Figure 6-23. Potential cottonwood habitat (green) and unsuitable cottonwood habitat (yellow, orange, and red). Frames show 

potential habitat at a base groundwater level (at discharge in Cherry Creek of 0.127 cms [4.5 cfs]), and at 30, 70, and 100 cm 

drawdowns. Area of potential habitat declines from 65 to 16 percent of the modeled floodplain area as a function of a 1-m drawdown below base level.
USDA Forest Service Gen. Tech. Rep. RMRS-GTR-282. 2012 117

Figure 6-24. Relationships between average flow (Q in cfs) calculated for each month 

during the growing season and related to cottonwood growth for each year. Only significant 

relationships are plotted. May: Growth (mm) = 0.28 + 0.033Q; r 2 = 0.25; P = 0.05. June: Growth 

(mm) = 0.23 + 0.056Q; r 2 = 0. 28; P = 0.03. July: Growth (mm) = 0.09 + 0.067Q; r 2 = 0.43; P = 

0.008. Relationships between April, August, and September flow and incremental growth were 

not significant (P>0.05). Vertical dotted lines indicate the median instream flow for each month 

(period of record).

Variability in growth rates of cottonwood and Goodding willow could be explained 

by differences in streamflow from year to year (Figure 6-24). Mean May, June, and July 

annual streamflow rates each explained most of the variability in tree growth rates. The 

median monthly instream flows filed for by the Forest Service would support intermediate 

growth rates of cottonwood and Goodding willow. Incremental reductions in flow would 

result in decreased cottonwood growth rates of 1.5, 3, and 3.5 mm per 5 cfs reduction 

in the months of May, June, and July. Similar reductions in Goodding willow growth 

were found. Cottonwood and Goodding willow are obligate phreatophytes; therefore, 

their health and persistence depend largely on maintenance of water tables within reach 

of their rooting zone. These linkages between streamflow and growth rates provided 

evidence that groundwater through the study reach is fed by streamflow. Analysis of 

groundwater levels across the valley and comparison of these fluctuations with surface 

water fluctuations and those measured at a streamflow gauge 15 km upstream further 

evidence a direct connection between groundwater levels and streamflow.

These findings suggest that the species comprising riparian forests along Cherry 

Creek depend on alluvial groundwater systems that are supported by and dependent 

upon streamflow in Cherry Creek. Maintenance of sufficient streamflow to support 

shallow water tables reduces the likelihood of conversion of cottonwood and Arizona 

sycamore-dominated forests to shrub communities and those more typical of upland and 

xeroriparian habitats. Reductions in streamflow and subsequent groundwater decline 

would suppress riparian forest species and favor non-native saltcedar and desert shrubs, 

resulting in a loss of riparian habitat. If the vegetation along Cherry Creek shifted from a 

cottonwood-willow-dominated riparian forest habitat to a saltcedar-burrobrush shrubland 

habitat, it would likely support mostly upland species found in adjacent xeroriparian 

areas instead of both riparian and upland species.
118 USDA Forest Service Gen. Tech. Rep. RMRS-GTR-282. 2012

Incremental reductions in streamflow would have negative consequences for riparian 

forest species and associated wildlife habitats including: (1) elevated water stress and 

decreased growth rates (fitness) of riparian tree species, (2) reduction in spatial extent 

of potential habitat for dominant forest species (e.g., cottonwood), and (3) likely conversion of complex riparian forest cover types to structurally and compositionally simple 

(or homogeneous) shrubland and bare cover types.

Acknowledgments

We thank Joyce Van De Water for assistance with the figures. Review and comments 

from Christopher Carlson, Joseph Gurrieri, Kristen Kaczynski, Rob Hubbard, John 

Potyondy, and Lindsay Reynolds improved this report. We also thank Vernon Bevan 

and Camille Febvre for critical review and for proofing the text.

Literature Cited

Adair, E. C., D. Binkley, and D. C. Andersen. 2004. Patterns of nitrogen accumulation and cycling in riparian floodplain ecosystems along the Green and Yampa Rivers. Oecologia 139: 108-116.

Alberta Agriculture and Food. 2004. Salinity Classification, Mapping and Management in Alberta. Alberta Agriculture and Agriculture Canada, Alberta, Canada. http://www1.agric.gov.ab.ca/$department/

deptdocs.nsf/all/sag3267.

Alstad, K. P., S. C. Hart, J. L. Horton and T. E. Kolb. 2008. Application of tree-ring isotopic analyses to 

reconstruct historical water use of riparian trees. Ecological Applications 18:421-437.

Arscott, D. B., K. Tockner, and J. V. Ward. 2003. Spatio-temporal patterns of benthic invertebrates along 

the continuum of a braided alpine river. Archiv Fur Hydrobiologie 158:431-460.

Auble, G. T., J. M. Friedman, and M. L. Scott. 1994. Relating riparian vegetation to present and future 

streamflows. Ecological Applications 4:544-554.

Auble, G. T., and M. L. Scott. 1998. Fluvial disturbance patches and cottonwood recruitment along the 

upper Missouri River, Montana. Wetlands 18:546-556.

Auble, G. T., M. L. Scott, and J. M. Friedman. 2005. Use of individualistic streamflow-vegetation relations 

along the Fremont River, Utah, USA to assess impacts of flow alteration on wetland and riparian areas. 

Wetlands 25:143-154.

Baker, W. L. 1990. Climatic and hydrologic effects on the regeneration of Populus angustifolia James along 

the Animas River, Colorado. Journal of Biogeography 17:59-73.

Baron, J. S., N. L. Poff, P. L. Angermeier, C. N. Dahm, P. H. Gleick, N. G. Hairston, R. B. Jackson, C. A. 

Johnston, B. D. Richter, and A. D. Steinman. 2002. Meeting ecological and societal needs for freshwater. 

Ecological Applications 12:1247-1260

Bedford, B. L., and K. S. Godwin. 2003. Fens of the United States: distribution, characteristics, and scientific 

connection versus legal isolation. Wetlands 23:608-629.

Bio/West, Inc. 1986. Final Report--Environmental evaluation for Sandhills Cooperative River basin study. 

Bio/West, Inc., Logan, Utah, USA.

Birken, A. S., and D. J. Cooper. 2006. Processes of Tamarix invasion and floodplain development along 

the lower Green River, Utah. Ecological Applications 16:1103-1120.

Blake, T. J., J. Sperry, T. Tschaplinski and S. Wang. 1996. Water relations. Pages 401-422 in R. Stettler, 

H. Bradshaw, P. Heilman and T. Hinkley, editors. Biology of Populus and its implications for management and conservation. NRC Research Press, National Research Council of Canada, Ottawa, Ontario.

Bohn, H.L. 1971. Redox potentials. Soil Science 112:39-45.

Bowden, W. B. 1987. The biogeochemistry of nitrogen in freshwater wetlands. Biogeochemistry 4:313-348.

Brinson, M. M. 1993. A hydrogeomorphic classification for wetlands. Technical Report WRP-DE-4. U.S. 

Army Engineer Waterways Experiment Station, Vicksburg, Mississippi, USA.

Brinson, M. M., and A. I. Malvarez. 2002. Temperate freshwater wetlands: types, status, and threats. Environmental Conservation 29:115-133.

Brown, D. J., W. A. Hubert, and S. H. Anderson. 1996. Beaver ponds create wetland habitat for birds in 

mountains of southeastern Wyoming. Wetlands 16:127-133

Brown, T.C. 2004. The marginal economic value of streamflow from National Forests. Discussion Paper 

DP-04-1, USDA Forest Service Proceedings RMRS-4851. Rocky Mountain Research Station, Fort 

Collins, Colorado, USA.

Buchanan, T. J., and W. P. Somers. 1976. Techniques of water-resources investigations of the United States 

Geological Survey. Applications of Hydraulics, Chapter A8, U.S. Geological Survey, Washington, DC, 

USA. Second edition.
USDA Forest Service Gen. Tech. Rep. RMRS-GTR-282. 2012 119

Bush, S.E., K.R. Hultine, J.S. Sperry, and J.R. Ehleringer. 2010. Calibration of thermal dissipation sap flow 

probes for ring- and diffuse-porous trees. Tree Physiology 30:1545-1555.

Busch, D. E., N. L. Ingraham, and S. D. Smith. 1992. Water uptake in woody riparian phreatophytes of the 

southwestern United States: a stable isotope study. Ecological Applications 2:450-459.

Busch, D. E. and S. D. Smith. 1995. Mechanisms associated with decline of woody species in riparian 

ecosystems of the southwestern U.S. Ecological Monographs 65:347-370.

Camporeale, C., and L. Ridolfi. 2006. Riparian vegetation distribution induced by river flow variability: a 

stochastic approach. Water Resources Research 42: W10415, doi:10.1029/2006WR004933.

Carsey, K., D. Cooper, K. Decker, D. Culver, and G. Kittel. 2003. Statewide wetlands classification and 

characterization—Final Report. Colorado Department of Natural Resources, Denver, Colorado, USA. 

Available: http://www.cnhp.colostate.edu/download/documents/2003/wetland_classification_final_report_2003.pdf.

Castelli, R. M., J. C. Chambers, and R. J. Tausch. 2000. Soil-plant relations along a soil-water gradient in 

great basin riparian meadows. Wetlands 20:251-266.

Caswell, H., editor. 2001. Matrix Population Models: Construction, Analysis, and Interpretation. Sinauer 

Associates, Inc., Sunderland, Massachusetts, USA.

Chadde, S. W., J. S. Shelly, R. J. Bursik, R. K. Moseley, A. G. Evenden, M. Mantas, F. Rabe, and B. 

Heidel. 1998. Peatlands on National Forests of the northern Rocky Mountains: ecology and conservation. USDA Forest Service Technical Report RMRS-GTR-11, Rocky Mountain Research Station, Fort 

Collins, Colorado, USA.

Chimner, R. A., and D. J. Cooper. 2003. Influence of water table levels on CO2 emissions in a Colorado 

subalpine fen: an in situ microcosm study. Soil Biology and Biochemistry 35:345-351.

Chimner, R. A., and D. J. Cooper. 2004. Using stable oxygen isotopes to quantify the water source used 

for transpiration by native shrubs in the San Luis Valley, Colorado USA. Plant and Soil 260:225-236.

Clearwater, M. J., F. C. Meinzer, J. L. Andrade, G. Goldstein and N. M. Holbrook. 1999. Potential errors 

in measurement of nonuniform sap flow using heat dissipation probes. Tree Physiology. 19:681-687.

Comer, P. S., S. Menard, M. Tuffly, K. Kindscher, R. Rondeau, G. Steinuaer, R. Schneider, and D. Ode. 

2003. Upland and wetland ecological systems in Colorado, Wyoming, South Dakota, Nebraska, and 

Kansas. Report and map to the National Gap Analysis Program. NatureServe, Arlington, Virginia, USA.

Cooper, D. J., and R. E. Andrus. 1994. Patterns of vegetation and water chemistry in peatlands of the westcentral Wind River Range, Wyoming, USA. Canadian Journal of Botany 72:1586-1597.

Cooper, D. J. 1996. Water and soil chemistry, floristics, and phytosociology of the extreme rich High Creek 

fen, in South Park, Colorado, U.S.A. Canadian Journal of Botany. 74: 1801-1811.

Cooper, D. J. and J. S. Sanderson. 1997. A montane Kobresia myosuroides fen community type in the 

Southern Rocky Mountains of Colorado, USA. Arctic and Alpine Research 29:300-303. 

Cooper, D. J., L. H. MacDonald, S. K. Wenger, and S. W. Woods. 1998. Hydrologic restoration of a fen in 

Rocky Mountain National Park, Colorado, USA. Wetlands 18:335-345.

Cooper, D. J., D. M. Merritt, D. C. Andersen, and R. A. Chimner. 1999. Factors controlling the establishment of Fremont cottonwood seedlings on the upper Green River, U.S.A. Regulated Rivers: Research 

and Management 15:419-440.

Cooper, D.J., D. D’Amico, and M.L. Scott. 2003. Physiological and morphological response patterns of 

Populus deltoides to alluvial groundwater pumping. Environmental Management 31:215-226.

Cooper, D. J., R. Andrus, and C. D. Arp. 2002. Sphagnum balticum in a southern Rocky Mountain iron 

fen. Madrono 49:186-188.

Cooper, D. J., D. C. Andersen, and R. A. Chimner. 2003a. Multiple pathways for woody plant establishment 

on floodplains at local to regional scales. Journal of Ecology 91:182-196.

Cooper, D.J., D. D’Amico, and M.L. Scott. 2003b. Physiological and morphological response patterns of 

Populus deltoides to alluvial groundwater pumping. Environmental Management 31:215-226.

Cooper, D. J., J. Dickens, N. T. Hobbs, L. Christensen, and L. Landrum. 2006. Hydrologic, geomorphic and 

climatic processes controlling willow establishment in a montane ecosystem. Hydrological Processes 

20:1845-1864.

Cooper, D. and E. Wolf. 2006. Yosemite Valley: Hydrologic Regime, Soils, Pre-Settlement vegetation, 

Disturbance and Concepts for Restoration. Unpublished Report to National Park Service, Yosemite 

National Park, CA.

Cooper, D. and L. Patterson. 2007. Restoration Plan for the Flagg Ranch, John D. Rockefeller Memorial 

Parkway, Wyoming. Unpublished Report to National Park Service, Grand Teton National Park, Moose, 

Wyoming.

Cooper, D. and E. Wolf. 2007. The influence of ground water pumping on wetlands in Crane Flat, Yosemite 

National Park, California. Unpublished Report to National Park Service, Yosemite National Park, CA.

Cooper, D.J., J.D. Lundquist, J. King, A. Flint, L. Flint, E. Wolf, and F.C. Lott. 2007. Effects of the Tioga 

Road on hydrologic processes and lodgepole invasion into Tuolumne Meadows, Yosemite National Park. 

Unpublished Report to National Park Service, Yosemite National Park, CA.
120 USDA Forest Service Gen. Tech. Rep. RMRS-GTR-282. 2012

Cowardin, L. M., V. Carter, and E. T. La Roe. 1979. Classification of wetlands and deepwater habitats of 

the United States. FWS/OBS-79/31. USDI Fish and Wildlife Service, Washington, D.C., USA.

Crawley, M. J. 1986. Life history and environment. Pages 253-290 in M. J.Crawley, editor. Blackwell 

Scientific Publications, London and Boston. 

Crum, H., and L. Anderson. 1981. Mosses of North America. Columbia University Press, New York, USA. 

Two volumes.

Davidson, A. S., and R. L. Knight. 2001. Avian nest success and community composition in a western 

riparian forest. Journal of Wildlife Management 65:334-344.

Disalvo, A. C., and S. C. Hart. 2002. Climatic and stream-flow controls on tree growth in a western montane 

riparian forest. Environmental Management 30:678-691.

Dixon, M. D. 2003. Effects of flow pattern on riparian seedling recruitment on sandbars in the Wisconsin 

River, Wisconsin, USA. Wetlands 23:125-139.

Dodd, J. D., and R. T. Coupland. 1966. Vegetation of saline areas in Saskatchewan. Ecology 47: 958-968.

Ehleringer, J. R., and C. B. Osmond. 1989. Stable isotopes. Pages 281-291 in R. W. Pearcy, J. Ehleringer, 

H. A. Mooney and P. W. Rundel, editors. 1989. Plant Physiological Ecology: field methods and instrumentation. Chapman and Hall, New York, USA.

Elzinga, C. L., D. W. Salzer, J. W. Willoughby, and J. P. Gibbs. 2001. Monitoring plant and animal populations. Blackwell Science, Inc., Malden, Massachusetts, USA.

FERC 1920. Federal Energy Regulatory Commission established under the Federal Power Act. Chapter 

12 of Title 16 of the United States Code, entitled “Federal Regulation and Development of Power”, 

Washington, D.C. 

Friedman, J. M., and V. J. Lee. 2002. Extreme floods, channel change, and riparian forests along ephemeral 

streams. Ecological Monographs 72:409-425.

Fall, P. 1997. Fire history and composition of the subalpine forest of western Colorado during the Holocene. 

Journal of Biogeography 24:309-325.

Ferris, J. G. 1963. Cyclic water-level fluctuations as a basis for determining aquifer transmissibility. Pages 

305-318 in R. Bentatl, R., editor. Methods of determining permeability, transmissibility and drawdown. 

USGS Water Supply Paper 1536-I, Washington, D.C., USA.

Francis, R. A., and A. M. Gurnell. 2006. Initial establishment of vegetative fragments within the active 

zone of a braided gravel-bed river (River Tagliamento, NE Italy). Wetlands 26:641-648.

Franz, E. H., and F. A. Bazzaz. 1977. Simulation of vegetation response to modified hydrologic regimes: a 

probablistic model based on niche differentiation in a floodplain forest. Ecology 58:176-183.

Friedman, J. M., and G. T. Auble. 1999. Mortality of riparian box elder from sediment mobilization and 

extended inundation. Regulated Rivers: Research and Management 15:463-476.

Friedman, J. M., G. T. Auble, E. D. Andrews, G. Kittel, R. F. Madole, E. R. Griffin, and T. M. Allred. 2006. 

Transverse and longitudinal variation in woody riparian vegetation along a montane river. Western North 

American Naturalist 66:78-91.

Friedman, J. M., and V. J. Lee. 2002. Extreme floods, channel change, and riparian forests along ephemeral 

streams. Ecological Monographs 72:409-425.

Graf, W. L. 1999. Dam nation: a geographic census of American dams and their large-scale hydrologic 

impacts. Water Resources Research 35:1305-1311

Gregory, S. V., F. J. Swanson, W. A. McKee, and K. W. Cummins. 1991. An ecosystem perspective of 

riparian zones. Bioscience 41:540-550.

Grime, J. P. 1977. Evidence for existence of 3 primary strategies in plants and its relevance to ecological 

and evolutionary theory. American Naturalist 111:1169-1194.

Grubb, P. J. 1977. The maintenance of species-richness in plant communities: the importance of the regeneration niche. Biological Reviews 52:107-145.

Harner, M. J., and J. A. Stanford. 2003. Differences in cottonwood growth between a losing and a gaining 

reach of an alluvial floodplain. Ecology 84:1453-1458.

Harrelson, C. C., C. L. Rawlins, and J. P. Potyondy. 1994. Stream channel reference sites: an illustrated 

guide to field technique. Gen.Tech. Rep. RM-245, Rocky Mountain Forest and Range Experiment Station, Fort Collins, Colorado, USA.

Haukos, D. A. 1992. Invertebrate herbivory in a Texas playa lake. Texas Journal of Science 44: 254-257.

Heidel, B., and S. Laursen. 2003. Botanical and ecological inventory of peatland sites on the Medicine Bow 

National Forest. Wyoming Natural Diversity Database, Laramie, Wyoming, USA.

Horton, J. L., and J. L. Clark. 2001. Water table decline alters growth and survival of Salix gooddingii and 

Tamarix chinensis seedlings. Forest Ecology and Management 140:239-247.

Horton, J. S., F. C. Mounts, and J. M. Kraft. 1960. Seed germination and seedling establishment of phreatophyte species. USDA Forest Service Station Paper 48, Rocky Mountain Forest and Range Experiment 

Station, Fort Collins, Colorado, USA.

Houle, G. 1994. Spatiotemporal patterns in the components of regeneration of four sympatric tree species-

-Acer rubrum, A. saccharum, Betula alleghaniensis and Fagus grandifolia. Journal of Ecology 82:39-53.
USDA Forest Service Gen. Tech. Rep. RMRS-GTR-282. 2012 121

Hubbard, R. M., J. Stape, M.G. Ryan, A. Almeida, and J. Rojas. 2010. Effects of irrigation on water use 

and water use efficiency in two fast growing eucalyptus plantations. Forest Ecology and Management 

259:1714-1721.

Hughes, F. M. R., T. Harris, K. Richards, G. Pautou, A. F. L. Hames, N. Barsoum, J. Girel, J. L. Peiry, and 

R. Foussadier. 1997. Woody riparian species response to different soil moisture conditions: laboratory 

experiments on Alnus incana (L.) Moench. Global Ecology and Biography Letters 6:247-256.

Hutchinson, G. E. 1957. Concluding remarks. Cold Spring Harbor Symposia on Quantitative Biology 

22:415–427. 

Jackson, P., F. Meinzer, G. Goldstein, N. Holbrook, J. Colvelier, and F. Rada. 1993. Environmental and 

physiological influences on carbon isotope composition of gap and understory plants in a lowland 

tropical forest. Chapter 9 in J. Ehleringer, A. Hall, and G. Farquhar, editors. Stable isotopes and plant 

carbon-water relations. Academic Press, New York, USA.

Jansson, R., C. Nilsson, M. Dynesius, and E. Andersson. 2000. Effects of river regulation on river-margin 

vegetation: a comparison of eight boreal rivers. Ecological Applications 10:203-224.

Johnson, W. C. 2000. Tree recruitment and survival in rivers: influence of hydrological processes. Hydrological Processes 14:3051-3074.

Johnson, W. C., T. L. Sharik, R. A. Mayes, and E. P. Smith. 1987. Nature and cause of zonation discreteness 

around glacial prairie marshes. Canadian Journal of Botany 65:1622-1632.

Jolly, I. D., G. R. Walker, and P. J. Thorburn. 1993. Salt accumulation in semiarid floodplain soils with 

implications for forest health. Journal of Hydrology 150:589-614.

Jongman, R., C. ter Braak, and O. Van Tongeren, editors. 1995. Data Analysis in Community and Landscape 

Ecology. Second edition. Cambridge University Press, Cambridge, United Kingdom.

Karrenberg, S., P. J. Edwards, and J. Kollmann. 2002. The life history of Salicaceae living in the active 

zone of floodplains. Freshwater Biology 47:733-748.

Kalra, A., T. C. Piechota, R. Davies, and G. A. Tootle. 2008. Changes in US streamflow and western US 

snowpack. Journal of Hydrologic Engineering 13:156-163.

Knighton, D. 1998. Fluvial Forms and Processes--A New Perspective. Arnold Publishing Co., London, 

United Kingdom.

Lambeck, R. J. 1997. Focal species: a multi-species umbrella for nature conservation. Conservation Biology 11:849-856.

Legendre, P., and L. Legendre, editors. 1998. Numerical Ecology. Second edition. Elsevier, Amsterdam, 

Netherlands.

Lenssen, J., F. Menting, W. Van Der Putten, and K. Blom. 1999. Control of plant species richness and 

zonation of functional groups along a freshwater flooding gradient. Oikos 86:523-534.

Lichvar, R. W. and J. T. Kartesz. 2012. North American Digital Flora: National Wetland Plant List, 

version 3.0 (http://wetland_plants.usace.army.mil).

Lins, H. F. 1997. Regional streamflow regimes and hydroclimatology. Water Resources Research 

33:1655-1667.

Lite, S. J., K. J. Bagstad, and J. C. Stromberg. 2005. Riparian plant species richness along lateral and 

longitudinal gradients of water stress and flood disturbance, San Pedro River, Arizona, USA. Journal of 

Arid Environments 63:785-813.

Lite, S. J. and J. C. Stromberg. 2005. Surface water and ground-water thresholds for maintaining PopulusSalix forests, San Pedro river, Arizona. Biological Conservation 125: 153-167.

Lytle, D. A., and D. M. Merritt. 2004. Hydrologic regimes and riparian forests: a structured population 

model for cottonwood. Ecology 85:2493-2503.

Mahoney, J. M., and S. B. Rood. 1998. Streamflow requirements for cottonwood seedling recruitment--an 

integrative model. Wetlands 18:634-645.

Manly, B. F. J., editor. 1994. Multivariate Statistical Methods: A Primer. Second edition. Chapman and 

Hall, London.

McClymont, A. F., J. W. Roy, M. Hayashi, L. R. Bentley, H. Maurer, and G. Langston. 2011. Investigating groundwater flow paths within proglacial moraine using multiple geophysical methods. Journal of 

Hydrology 399:57-69.

McCune, B., and J. B. Grace. 2002. Analysis of Ecological Communities. MJM Press, Gleneden Beach, 

Oregon, USA. 304 pages.

McCune, B, and M. J. Mefford. 1999. PC-ORD, Multivariate analysis of ecological data. Fourth edition. 

MjM Software Design, Gleneden Beach, Oregon, USA.

Merigliano, M. F. 2005. Cottonwood understory zonation and its relation to floodplain stratigraphy. Wetlands 25:356-374.

Merritt, D. M., and D. J. Cooper. 2000. Riparian vegetation and channel change in response to river regulation: a comparative study of regulated and unregulated streams in the Green River basin, USA. Regulated 

Rivers: Research and Management 16:543-564.
122 USDA Forest Service Gen. Tech. Rep. RMRS-GTR-282. 2012

Merritt, D. M., M. L. Scott, N. L. Poff, G. T. Auble, and D. A. Lytle. 2010a. Theory, methods and tools 

for determining environmental flows for riparian vegetation: riparian vegetation-flow response guilds. 

Freshwater Biology 55:206-225.

Merritt, D. M., H. L. Bateman, and C. D. Peltz. 2010b. Instream flow requirements for maintenance of 

wildlife habitat and riparian vegetation: Cherry Creek, Tonto National Forest, Arizona. A report submitted to the Tonto National Forest by USDA Forest Service Stream Systems Technology Center, Fort 

Collins, Colorado, USA.

Merritt, D. M., and N. L. Poff. 2010. Shifting dominance of riparian Populus and Tamarix along gradients 

of flow alteration in western North American rivers. Ecological Applications 20:135-152. 

Mills, G. C., J. B. Dunning, Jr., and J. M. Bates. 1991. The relationship between breeding bird density and 

foliage volume. Wilson Bulletin 103:468-479.

Mitsch, W. J., and J. G. Gosselink. 2000. Wetlands. Third edition. John Wiley, New York, USA. 

Montgomery, D. M. 1999. Process domains and the river continuum. Journal of the American Water Resources Association 35:397-410.

Mueller-Dombois, D., and H. Ellenberg. 1974. Aims and Methods of Vegetation Ecology. The Blackburn 

Press, Caldwell, New Jersey, USA.

Naiman, R. J., and H. Decamps. 1997. The ecology of interfaces: riparian zones. Annual Review of Ecology and Systematics 28:621-658.

Naiman, R. J., H. DeCamps, and M. Pollack. 1993. The role of riparian corridors in maintaining regional 

biodiversity. Ecological Applications 3:209-212. 

National Research Council. 1995. Wetlands: Characteristics and Boundaries. National Academy Press, 

Washington, DC, USA.

National Research Council. 2002. Riparian Areas: Functions and Strategies for Management. National 

Academy Press, Washington DC, USA

Naumburg, E., R. Mata-Gonzalez, R.G. Hunter, T. Mclendon, and D.W. Martin. 2005. Phreatophytic vegetation and groundwater fluctuations: a review of current research and application of ecosystem response 

modeling with an emphasis on Great Basin vegetation. Environmental Management 35:726-740.

Nelson, R. W., W. J. Logan, and E. C. Weller. 1984. Playa wetlands and wildlife on the Southern Great 

Plains: A characterization of habitat. U.S. Environmental Protection Agency, Washington, DC, USA. 

Nilsson, C., A. Ekblad, M. Gardfjell, and B. Carlberg. 1991. Long-term effects of river regulation on river 

margin vegetation. Journal of Applied Ecology 28:963-987.

Nilsson, C., A. Ekblad, M. Dynesius, S. Backe, M. Gardfjell, B. Carlberg, S. Hellqvist, and R. Jansson. 

1994. A comparison of species richness and traits of riparian plants between a main channel and its 

tributaries. Journal of Ecology 82:281-295. 

Nilsson, C., and M. Svedmark. 2002. Basic principles and ecological consequences of changing water 

regimes: riparian plant communities. Environmental Management 30:468-480.

Novitzki, R. 1978. Hydrologic characteristics of Wisconsin wetlands, and their influence on floods, stream 

flow and sediment. Pages 377-388, in Wetland functions and values: the state of our understanding. 

American Water Resources Association. 

Novitski, R.P 1982. Hydrology of Wisconsin Wetlands. University of Wisconsin Extension Geological 

Natural History Survey Circular 40, University of Wisconsin, Madison, 22 pp.

Olden, J. D., and N. Poff, L. 2003. Redundancy and the choice of hydrologic indices for characterizing 

streamflow regimes. River Research and Applications 19:101-121.

Oren, R., J. S. Sperry, et al. 1999. Survey and synthesis of intra- and interspecific variation in stomatal 

sensitivity to vapour pressure deficit. Plant Cell and Environment 22(12):1515-1526.

Palmer, W. C. 1965. Meteorological drought. U.S. Weather Bureau Research Paper No. 45, Washington, 

DC, USA.

Patten, D. T. 1998. Riparian ecosystems of semi-arid North America: diversity and human impacts. Wetlands 18:498-512.

Pearcy, R. W., J. Ehleringer, H. A. Mooney and P. W. Rundel, editors. 1989. Plant Physiological Ecology: 

field methods and instrumentation. Chapman and Hall, New York, USA.

Pinay, G., J. C. Clement, R.J. Naiman. 2002. Basic principles and ecological consequences of changing 

water regimes on nitrogen cycling in fluvial systems. Environmental Management 30:481-491.

Pinay, G., B. Gumiero, E. Tabacchi, O. Gimenez, A. M. Tabacchi-Planty, M. M. Hefting, T. P. Burt, V. A. 

Black, C. Nilsson, V. Iordache, F. Bureau, L. Vought, G. E. Petts, and H. Décamps. 2007. Patterns of 

denitrification rates in European alluvial soils under various hydrological regimes. Freshwater Biology 

52:252-266.

Pinay, G., and R. J. Naiman. 1991. Short-term hydrologic variations and nitrogen dynamics in beaver created meadows. Archiv Fur Hydrobiologie 123:187-205.

Pockman, W. T. and J. S. Sperry. 2000. Vulnerability to xylem cavitation and the distribution of Sonoran 

desert vegetation. American Journal of Botany 87:1287-1299.
USDA Forest Service Gen. Tech. Rep. RMRS-GTR-282. 2012 123

Pollock, M. M. 1998. Biodiversity. Page 705 in R. J. Naiman and R. E. Bilby, editors. River Ecology and 

Management Lessons from the Pacific Coast Eco-region. Springer-Verlag, New York, USA.

Poff, N. L. 1996. A hydrogeography of unregulated streams in the United States and an examination of 

scale-dependence in some hydrological descriptors. Freshwater biology 36:71-91.

Pringle, C. M. 2000. Threats to US public lands from cumulative hydrologic alterations outside of their 

boundaries. Ecological Applications 10:971-989.

Rains, M. C., J. E. Mount, and E. W. Larsen. 2004. Simulated changes in shallow groundwater and vegetation distributions under different reservoir operations scenarios. Ecological Applications 14:192-207.

Rathburn, S. L., D. M. Merritt, E. E. Wohl, J. A. Sanderson, and H. A. L. Knight. 2009. Characterizing 

environmental flows for maintenance of river ecosystems: North Fork Cache La Poudre River, Colorado. 

Pages 143-157 in L. A. James, S. L. Rathburn, and G. R. Whittecar, editors. Management and restoration 

of fluvial systems with broad historical changes and human impacts. Geological Society of America 

Special Paper, 451.

Raunkiær, C. 1934. The life forms of plants and statistical plant geography. Oxford University Press, 

Oxford, United Kingdom.

Reed, P. B. 1988. National list of plant species that occur in wetlands: national summary. U.S. Fish and 

Wildlife Service Biological Report 88. U.S. Fish and Wildlife Service, Washington, DC, USA.

Renofalt, B. M., D. M. Merritt, and C. Nilsson. 2007. Connecting variation in vegetation and stream flow: 

the role of geomorphic context in vegetation response to large floods along boreal rivers. Journal of 

Applied Ecology 44:147-157.

Richter, B. D., J. V. Baumgartner, R. Wigington, and D. P. Braun. 1997. How much water does a river 

need? Freshwater Biology 37:231-249.

Richter, B. D., R. Mathews, and R. Wigington. 2003. Ecologically sustainable water management: managing river flows for ecological integrity. Ecological Applications 13:206-224. 

Rood, S. B., L. A. Goater, J. M. Mahoney, C. M. Pearce, and D. G. Smith. 2007. Floods, fire, and ice: 

disturbance ecology of riparian cottonwoods. Canadian Journal of Botany--Revue Canadienne De 

Botanique 85:1019-1032.

Rood, S. B., C. R. Gourley, E. M. Ammon, L. G. Heki, J. R. Klotz, M. L. Morrison, D. Mosley, G. G. 

Scoppettone, S. Swanson, and P. L. Wagner. 2003. Flows for floodplain forests: a successful riparian 

restoration. Bioscience 53:647-656.

Rood, S., S. Patino, K. Coombs, and M. Tyree. 2000. Branch sacrifice: cavitation-associated drought 

adaptation of riparian cottonwoods. Trees 14:248-257.

Rood, S. B., G. M. Samuelson, J. H. Braatne, C. R. Gourley, F. M. R. Hughes, and J. M. Mahoney. 2005. 

Managing river flows to restore floodplain forests. Frontiers in Ecology and the Environment 3:193-201.

Scott, M. L., G. T. Auble, and J. M. Friedman. 1997. Flood dependency of cottonwood establishment along 

the Missouri River, Montana, USA. Ecological Applications 7:677-690.

Scott, M. L., J. M. Friedman, and G. T. Auble. 1996. Fluvial process and the establishment of bottomland 

trees. Geomorphology 14:327-339.

Scott, M. L., P. B. Shafroth, and G. T. Auble. 1999. Responses of riparian cottonwoods to alluvial water 

table declines. Environmental Management 23:347-358.

Scott, M. L., M. A. Wondzell, and G. T. Auble. 1993. Hydrograph characteristics relevant to the establishment and growth of western riparian vegetation: 237-246. Hydrology Days Publications, Atherton, 

California, USA.

Seabloom, E. W., A. G. Van Der Valk, and K. A. Moloney. 1998. The role of water depth and soil temperature in determining initial composition of prairie wetland coenoclines. Plant Ecology 138:203-216.

Segelquist, C.A., M. L. Scott, and G. T. Auble. 1993. Establishment of Populus deltoides under simulated 

alluvial groundwater declines. American Midland Naturalist 130:274-285.

Shafroth, P. B., G. T. Auble, J. C. Stromberg, and D. T. Pattern. 1998. Establishment of woody riparian 

vegetaion in relation to annual patterns of streamflow, Bill Williams River, Arizona. Wetlands 18:577-590.

Shaw, J., and D. J. Cooper. 2008. Watershed and stream reach characteristics controlling riparian vegetation 

in semiarid ephemeral stream networks. Journal of Hydrology 350:68-82.

Shipley, B., P. A. Keddy, and L. P. Lefkovitch. 1991. Mechanisms producing plant zonation along a water 

depth gradient: a comparison with the exposure gradient. Canadian Journal of Botany 69:1420-1424.

Smith, L. M., and D. A. Haukos. 2002. Floral diversity in relation to playa wetland area and watershed 

disturbance. Conservation Biology 16:964-974.

Smith, L. M., and J. A. Kadlec. 1983. Seed banks and their role during drawdown of a North American 

marsh. Journal of Applied Ecology 20:673-684

Smith, R. D., A. Ammann, C. Bartoldus, and M. M. Brinson. 1995. An approach for assessing wetland 

functions using hydrogeomorphic classification, reference wetlands, and functional indices. United States 

Army Corps of Engineers Technical Report WRP-DE-9. U.S. Army Engineer Waterways Experiment 

Station, Vicksburg, Mississippi, USA.
124 USDA Forest Service Gen. Tech. Rep. RMRS-GTR-282. 2012

Smith, S. D., D. A. Devitt, A. Sala, J. R. Cleverly, and D. E. Busch. 1998. Water relations of riparian plants 

from warm desert regions. Wetlands 18:687-696.

Sperry, J. S. 1995. Limitations on stem water transport and their consequences. Pages ??? in B. L. Gartner 

editor. Plant stems:physiology and functional morphology. Academic Press, San Diego, USA.

Sperry, J. S. 2000. Hydraulic constraints on plant gas exchange. Agricultural and Forest Meteorology 

104:13-23.

Steppe, K., D. DePauw, T. Doody, and R. O. Teskey. 2010. A comparison of sap flux density using thermal 

dissipation, heat pulse velocity and heat field deformation methods. Agricultural and Forest Meteorology 150:1046-1056.

Stromberg, J. C., V. B. Beauchamp, M. D. Dixon, S. J. Lite and C. Paradzick. 2007a. Importance of lowflow and high-flow characteristics to restoration of riparian vegetation along rivers in and south-western 

United States. Freshwater Biology 52:651-679.

Stromberg, J. C., S. J. Lite, R. Marler, C. Paradzick, P. B. Shafroth, D. Shorrock, J. M. White, and M. S. 

White. 2007b. Altered stream-flow regimes and invasive plant species: the Tamarix case. Global Ecology and Biogeography 16:381-393.

Stromberg, J. C., and D. T. Patten. 1990. Riparian vegetation instream flow requirements: a case study from 

a diverted stream in the eastern Sierra Nevada, California, USA. Environmental Management 14:185-194.

Stromberg, J. C., and D. T. Patten. 1991. Instream flow requirements for cottonwoods at Bishop Creek, 

Inyo County, California, USA. Rivers 2:1-11.

Stromberg, J. C., and D. T. Patten. 1996. Instream flow and cottonwood growth in the eastern Sierra Nevada 

of California, USA. Regulated Rivers: Research and Management 12:1-12.

Stromberg, J.C., B. D. Richter, D. T. Patten, and L.G. Wolden. 1993. Response of a Sonoran riparian forest 

to a 10-year return flood. Great Basin Naturalist 53:118-130.

Szaro, R. C. 1990. Southwestern riparian plant communities: site characteristics, tree species distributions, 

and size-class structures. Forest Ecology and Management 33/34:315-334.

Taneda, H., and J. S. Sperry. 2008. A case-study of water transport in co-occurring ring- versus diffuseporous trees: contrasts in water-status, conducting capacity, cavitation and vessel refilling. Tree Physiology 28:1641-1651.

Thormann, M. N., A. R. Szumigalski, and S. E. Bayley. 1999. Aboveground peat and carbon accumulation 

potentials along a bog-fen-marsh wetland gradient in southern boreal Alberta, Canada. Wetlands 19:305-317.

Tiner, R. W. 1984. Wetlands of the United States: current status and recent trends. USDI Fish and Wildlife 

Service, National Wetlands Inventory, Washington, DC, USA.

Tyree, M., and J. Sperry. 1989. Vulnerability of xylem to cavitation and embolism. Annual Review of Plant 

Physiology and Plant Molecular Biology 40:19-36.

Tyree, M. T., K. J. Kolb, S. J. Rood, and S. Patino. 1994. Vulnerability to drought induced cavitation of riparian 

cottonwoods in Alberta: a possible factor in the decline of the ecosystem? Tree Physiology 14:455-466.

Ungar, I. A. 1966. Salt tolerance of plants growing in saline areas of Kansas and Oklahoma. Ecology 

47:154-162.

Ungar, I. A. 1974. Halophyte communities of Park County, Colorado. Bulletin of the Torrey Botanical 

Club 101:145-152.

U.S. Army Corps of Engineers. 2009. Mountains and plains regional supplement to the Corps of Engineers 

wetland delineation manual: western mountains, valleys, and coast region (Version 2.0). U.S. Army 

Engineer Research and Development Center Environmental Laboratory, Vicksburg, Mississippi, USA.

Van der Valk, A. G., and C. B. Davis. 1976. Seed banks of prairie glacial marshes. Canadian Journal of 

Botany 54:1832-1838. 

Van der Valk, A.G., L. Squires, C.H. Welling.1994. Assessing the impacts of an increase in water-level on 

wetland vegetation. Ecological Applications 4:525-534.

Vanderijt, C., L. Hazelhoff, and C. Blom. 1996. Vegetation zonation in a former tidal area: a vegetation-type 

response model based on DCA and logistic regression using GIS. Journal of Vegetation Science 7:505-518.

Waddle, T. J., and K. D. Bovee. 2009. Environmental flows studies of the Fort Collins Science Center, U.S. 

Geological Survey: Cherry Creek, Arizona. U.S. Geological Survey Reston, Virginia, USA.

Wafer, C. C., J. B. Richards, and D. L. Osmond. 2004. Construction of platinum-tipped redox probes for 

determining soil redox potential. Journal of Environmental Quality 33:2375-2379.

Weber, W. A., and R. Wittmann. 2001. Colorado flora, western slope. Colorado Associated University 

Press, Niwot, Colorado, USA.

Weltzin, J. F., J. Pastor, C. Harth, S. D. Bridgham, K. Updegraff, and C. T. Chapin. 2000. Response of bog 

and fen plant communities to warming and water-table manipulations. Ecology 81:3464-3478.

Westbrook, C., D. J. Cooper, B. Baker. 2006. Beaver dams and overbank floods influence groundwatersurface water interactions of a Rocky Mountain riparian area. Water Resources Research 42:W06404. 

doi:10.1029/2005WR004560. 
USDA Forest Service Gen. Tech. Rep. RMRS-GTR-282. 2012 125

Williams, C. A. and D. J. Cooper. 2005. Mechanisms of riparian cottonwood decline along regulated rivers. Ecosystems 8:382-395.

Willms, J., S. B. Rood, W. Willms, and M. Tyree. 1998. Branch growth of riparian cottonwoods: a hydrologically sensitive dendrochronological tool. Trees--Structure and Function 12:215-223.

Wilson, S. D., D. R. J. Moore, and P. A. Keddy. 1993. Relationships of marsh seed banks to vegetation 

patterns along environmental gradients. Freshwater Biology 29:361-370.

Winter, T. C., J. W. Harvery, O. L. Franke, and W. M. Alley. 1996. Ground water and surface water, 

a simple resource. USGS Circular 1139.

Winter, T. C., 1989. Hydrologic studies of wetlands in the northern prairie. Pages 16-54 in A. Van Der Valk, 

editor. Northern Prairie Wetlands. Iowa State University Press, Ames, Iowa, USA

Winter, T. C. 1999. Relation of Streams, Lakes, and Wetlands to Groundwater Flow Systems. Hydrogeology Journal 7:28-45.

Winter, T. C. 2001. The concept of hydrologic landscapes. Journal of the American Water Resources Association 37:335-349.

Winter, T. C., and D. O. Rosenberry. 1998. Hydrology of prairie pothole wetlands during drought and 

deluge: a 17-year study of the Cottonwood Lake wetland complex in North Dakota in the perspective of 

longer term measured and proxy hydrological records. Climatic Change 40:189-209.

Winter, T. C., D. O. Rosenberry, D. C. Buso, and D. A. Merk. 2001. Water source to four U.S. wetlands: 

implications for wetland management. Wetlands 21: 462-473.

Wohl, E. E. 2000. Mountain Rivers. American Geophysical Union, Washington, DC, USA.

Wurster, F. C., D. J. Cooper, and W. E. Sanford. 2003. Stream/aquifer interactions at Great Sand Dunes 

National Monument, Colorado: influences on interdunal wetland disappearance. Journal of Hydrology 

271:77-100.


The Rocky Mountain Research Station develops scientific information and 

technology to improve management, protection, and use of the forests and 

rangelands. Research is designed to meet the needs of the National Forest 

managers, Federal and State agencies, public and private organizations, 

academic institutions, industry, and individuals. Studies accelerate solutions to 

problems involving ecosystems, range, forests, water, recreation, fire, resource 

inventory, land reclamation, community sustainability, forest engineering 

technology, multiple use economics, wildlife and fish habitat, and forest insects 

and diseases. Studies are conducted cooperatively, and applications may be 

found worldwide.

Station Headquarters

Rocky Mountain Research Station 

240 W Prospect Road

Fort Collins, CO 80526 

(970) 498-1100

Research Locations

Reno, Nevada

Albuquerque, New Mexico

Rapid City, South Dakota

Logan, Utah

Ogden, Utah

Provo, Utah

The U.S. Department of Agriculture (USDA) prohibits discrimination in all of its programs 

and activities on the basis of race, color, national origin, age, disability, and where 

applicable, sex (including gender identity and expression), marital status, familial status, 

parental status, religion, sexual orientation, political beliefs, genetic information, reprisal, 

or because all or part of an individual’s income is derived from any public assistance 

program. (Not all prohibited bases apply to all programs.) Persons with disabilities who 

require alternative means for communication of program information (Braille, large print, 

audiotape, etc.) should contact USDA’s TARGET Center at (202) 720-2600 (voice and 

TDD).

To file a complaint of discrimination, write to: USDA, Assistant Secretary for Civil Rights, 

Office of the Assistant Secretary for Civil Rights, 1400 Independence Avenue, S.W., Stop 

9410, Washington, DC 20250-9410.

Or call toll-free at (866) 632-9992 (English) or (800) 877-8339 (TDD) or (866) 377-8642 

(English Federal-relay) or (800) 845-6136 (Spanish Federal-relay). USDA is an equal 

opportunity provider and employer.

Flagstaff, Arizona

Fort Collins, Colorado

Boise, Idaho

Moscow, Idaho

Bozeman, Montana

Missoula, Montana

To learn more about RMRS publications or search our online titles:

www.fs.fed.us/rm/publications

www.treesearch.fs.fed.us

Federal Recycling Program Printed on Recycled Paper

www.fs.fed.us/rmrs